Jobs

15
  • Β· 91 views Β· 8 applications Β· 25d

    Data Scientist / Quantitative Researcher

    Full Remote Β· Worldwide Β· Product Β· 3 years of experience
    We are Onicore β€” fintech company specializing in developing products for cryptocurrency operations. Registered in the USA, our company is powered by a talented Ukrainian team, working across the globe. Now we’re on the hunt for a specialist who will...

    We are Onicore β€” fintech company specializing in developing products for cryptocurrency operations. 

    Registered in the USA, our company is powered by a talented Ukrainian team, working across the globe.
     

    πŸ“Š Now we’re on the hunt for a specialist who will drive the project of algorithmic trading

     

    Your skills:

    - 3+ years of experience in Data Science;

    - excellent command of Python, understanding of the principles of OOP;

    - deep knowledge in linear algebra, probability theory and mathematical statistics;

    - data collection and preprocessing (numpy, pandas, scikit-learn,ta-lib);

    - experience working with all types of classical machine learning (Supervised Learning, Unsupervised Learning, Reinforcement Learning);

    - development experience and deep understanding of the principles of the architectures: RNN, LSTM, GRU, CNN, Transformer in the field of analysis and prediction of time sequences (time series predictions);

    - confident use of both high-level and low-level APIs for TensorFlow (writing custom training loops, custom metrics & loss_functions). 

    Knowledge of PyTorch is welcome;

    - the ability to visualize the learning process using TensorBoard;

    - boosting neural networks (Distributed XGBoost/LightGBM);

    - visualization of results (matplotlib, seaborn).

     

    Would be a plus:

    - experience with currency markets;

    - PhD degree in the field of data science / machine learning.

     

    Your responsibilities:

    ● solving algorithmic trading problems: regression/autoregression, classification of timeseries/financial series, working with cryptocurrency quotes.


    What’s in it for you? 

    πŸ₯ Health first: Comprehensive medical insurance.

    πŸ€“ Keep growing: We cover courses, conferences, training sessions, and workshops.

    πŸ’ͺ Stay active mentally and physically : Sports / hobby / personal psychologist to fuel yourself.

    πŸ’Ό We've got your back: Access to legal assistance when you need it.

    πŸ§—β€β™‚οΈ Inspiring vibes: Join a motivated, goal-oriented team that supports each other.

    πŸ§‘β€πŸ’» Make a difference: Have a direct impact on shaping and growing the product.

    πŸ’» Work smarter: Corporate laptops to help you do your best work.


    Join our team and help us level up!

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  • Β· 49 views Β· 8 applications Β· 17d

    ML Computer Vision Engineer (machine learning engineer) to $5500

    Full Remote Β· Countries of Europe or Ukraine Β· Product Β· 3 years of experience Β· Upper-Intermediate
    We are elai.io, an innovative AI-driven startup specializing in video generation. Recently acquired by Panopto β€” a leader in interactive video solutions β€” we’re now part of a growing team of around 200 professionals focused on advancing learning through...

    We are elai.io, an innovative AI-driven startup specializing in video generation.

     

    Recently acquired by Panopto β€” a leader in interactive video solutions β€” we’re now part of a growing team of around 200 professionals focused on advancing learning through powerful, interactive video technology.

     

    What You’ll Do as a Computer Vision Engineer:
    1. Research, design and implement appropriate computer vision algorithms for the main product (generating video);
    2. Research, find and use appropriate datasets;
    3. Define quality metrics, run machine learning experiments, and analyse results;
    4. Be on top of industry trends, research and propose new technologies.

     

    Our ideal candidate has:
    1. post-doc, PhD or Master’s degree in Computer Science or similar field;
    2. proven experience as a Machine Learning Engineer or similar role;
    3. deep knowledge of maths, probability, linear algebra, computer vision and algorithms;
    4. 3+ years of experience with Python;
    5. 2+ years of experience with PyTorch (TensorFlow experience is a plus);
    6. familiarity with state of the art networks, architectures and models in computer vision area (like UNet, Resnet, GAN, Transformers, Diffusion Models, NeRF, etc.);
    7. experience in deploying machine learning algorithms in production Base knowledge: git, docker, linux, bash;
    8. experience in 3d graphics or game development would be a great plus.

     

    We offer:
    1. Opportunity to work with a highly qualified international and friendly team
    2. Decent and timely payment fixed in USD
    3. The most flexible work schedule, including remote work
    4. Unlimited time off

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  • Β· 26 views Β· 4 applications Β· 26d

    Game Mathematician

    Full Remote Β· EU Β· Product Β· 3 years of experience Β· Upper-Intermediate
    We are looking for an experienced and driven Game Mathematician to join our client's Game Studio. What You Will Do: The Game Mathematician will work closely with the Senior Management and Game Design Teams to develop concepts and statistical documents...

    We are looking for an experienced and driven Game Mathematician to join our client's Game Studio.

     

    What You Will Do:

    The Game Mathematician will work closely with the Senior Management and Game Design Teams to develop concepts and statistical documents for unique gambling games. Such games may be traditional video slot games, table games or multiplayer casual-mobile style games that will contain a gambling element. This role will be working collaboratively with the other disciplines of the Games Inc team to ensure that slot games are not only entertaining but also fair and financially viable for the casino. Playing a vital role in balancing the interests of players and the casino while complying with industry regulations. A Game Mathematician will leverage their passion for playing various genres of games as well as developing their expert knowledge of player psychology to help devise unique and engaging Game content. You will help to create and maintain comprehensive documentation, create detailed experience flowcharts, wireframes, and detailed moment-to-moment gameplay experiences with distinct clarity. Additionally, the Game Mathematician will assist in the brainstorming, creation, and review of new game features for the Company’s future product line.

     

    Summary of Responsibilities:

    • Collaborate with the slots team to assist in the design and creation of unique gambling games;
    • Use mathematical models to create game rules, pay tables and volatility settings;
    • Consistently demonstrate an increasing knowledge of the gaming market and an empathy for all player types;
    • Help with the Mathematical Analysis of existing and new games to analyse the probability of winning and the expected return to the player for each game. Calculate the house edge and volatility of the games to ensure profitability for the casino. Optimising game parameters to achieve desired player engagement and revenue targets;
    • Ensure the integrity of the random number generator (RNG) used in slot games to guarantee fair and unpredictable outcomes;
    • Stay up-to-date with gaming regulations and ensure that all games meet legal requirements and standards;
    • Collect and analyse data from slot games to make data-driven decisions for game improvements;
    • Monitor and interpret player behaviour and game performance to identify areas for enhancement;
    • Conduct playtesting and quality assurance to identify and address issues with game mechanics or payouts;
    • Ensure that the game provides a satisfying player experience while adhering to the intended mathematical model;
    • Maintain detailed documentation of game specifications, mathematical models, and testing results.

    What you'll need to have:

    • Ability to build a greater knowledge of real money casino games, player psychology and the ability to help in the creation of ideas and designs for specific markets and players;
    • Understanding of the basic mathematical fundamentals of gambling games;
    • Passion for games and mobile gaming, including an understanding of mobile gambling products and trends;
    • Excellent written and verbal communication skills;
    • Familiarity with software tools used for game development and analysis;
    • Ability to work in a collaborative, multi-team environment, including product managers, engineers, artists, marketing, and support service personnel;
    • Good organisational, problem-solving and interpersonal skills.

    Other Duties and Responsibilities:

    • Participation in team brainstorming;
    • Contributing to the review of other designers’ games and concepts;
    • Contributing to the evolution of the team’s process and best practices;
    • Market and data analysis of current trends;
    • Assist with strategising future product plans and lines.

    Qualifications:

    • Experience designing games, including math or similar products that come into being through various channels, including original concepts, competitively relevant products, and business or market needs;
    • Knowledge or experience with various game development pipelines & methodologies;
    • Involvement within teams developing products is highly recommended;
    • Knowledge about games and/or the casino industry, including the current market landscape
    • Experience working with multiple disciplines, including artists, mathematicians, software developers, etc., in creating games or products.

    The company offers:

    • Time off: 25 days of annual leave per year are available;
    • Sick Leave & Public Holidays: Entitlement includes UK public holidays and statutory sick leave;
    • Flexible Working Hours: Flexible scheduling is supported to allow effective time management;
    • Remote work: Remote work is a great benefit and offers flexibility, helps improve work-life balance, and supports productivity across different locations;
    • Referral program: Great people know great people. Help grow the team by referring talented individuals who would be a strong fit!;
    • Employee Education Initiative: Twice a year, the company provides an opportunity to explore new interests outside of daily work, fostering curiosity and personal development;
    • Professional Development: Courses, conferences, workshops, and training programs that benefit both the employee and the company may be fully funded.

    If you find this opportunity right for you, don't hesitate to apply or get in touch with us if you have any questions!

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  • Β· 42 views Β· 0 applications Β· 1d

    Data Scientist (NLP + LLMs)

    Full Remote Β· Ukraine Β· 3 years of experience
    We are looking for a Data Scientist (NLP & LLMs) to join our team and work on the development of AI-powered solutions using modern NLP, Deep Learning, and multi-agent systems. Project description: We are building AI-driven fintech solutions using...

    We are looking for a Data Scientist (NLP & LLMs) to join our team and work on the development of AI-powered solutions using modern NLP, Deep Learning, and multi-agent systems.

     

    Project description:

     

    We are building AI-driven fintech solutions using LLMs, RAG, and autonomous agents to automate compliance, contracts, and risk analysis β€” streamlining workflows and boosting decision-making with intelligent insights.

     

    Requirements:

     

    • 3+ years of experience as a Data Scientist or in a related role
    • Strong knowledge of Deep Learning and Natural Language Processing (NLP)
    • Hands-on experience with Large Language Models (LLMs), RAG, and multi-agent systems
    • Proficiency in Python and relevant libraries such as PyTorch, TensorFlow, Transformers
    • Solid foundation in Computer Science, Mathematics, or Statistics (Bachelor’s or higher)

     

    Responsibilities:

     

    • Develop NLP tools for automated contract generation, review, and compliance analysis
    • Build AI agents to generate and update legal documents based on input and regulations
    • Implement systems for legal clause classification and risk/highlight detection
    • Create pipelines for legal request analysis and decision support (e.g., asset seizure)
    • Collaborate with legal teams to fine-tune models and balance AI vs rule-based outputs
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  • Β· 21 views Β· 2 applications Β· 1d

    Machine Learning Engineer

    Full Remote Β· Worldwide Β· 3 years of experience Β· Upper-Intermediate
    We are toogeza, a Ukrainian recruiting company that is focused on hiring talents and building teams for tech startups worldwide. People make a difference in the big game, we may help to find the right ones. Currently, we are looking for a ML Engineer for...

    We are toogeza, a Ukrainian recruiting company that is focused on hiring talents and building teams for tech startups worldwide. People make a difference in the big game, we may help to find the right ones.

    Currently, we are looking for a ML Engineer for The Playa

    Location: Remote

    Job Type: Full-Time


    About our client:

    The Playa helps iGaming platforms boost engagement, revenue, and ROMI by up to 25% by understanding and profiling player behavior, detecting positive and suspicious activities, and delivering tailored recommendations to each player.

    More information about The Playa solutions can be found on www.theplaya.solutions


    Role Overview:

    We are looking for an experienced Machine Learning Engineer to build, deploy, and maintain machine learning solutions that are ready for production. In this role, you will solve challenging problems, develop recommendation systems, and improve machine learning workflows to deliver real-world impact.


    Responsibilities:

    • Design, create, and deploy machine learning models for regression, classification, and clustering.
    • Develop and improve recommendation systems to meet business needs.
    • Write clean, efficient, and scalable code in Python.
    • Use AWS tools and services to build reliable, cloud-based machine learning solutions.
    • Manage workflows with Airflow and handle containerized environments using Docker.
    • Write and optimize SQL queries for data extraction, transformation, and analysis.
    • Work with the team to follow best practices in version control (Git) and testing.
    • Apply basic MLOps practices to improve machine learning processes.


    Requirements:


    Must-Have Skills:

    • At least 3 years of hands-on experience in machine learning and data science.
    • Strong skills in Python, SQL, and Git.
    • Hands-on experience with cloud platforms (preferably AWS), workflow orchestration using Airflow, and containerization with Docker.
    • Good understanding of machine learning techniques, such as regression, classification, and clustering.
    • Proven ability to deliver robust, scalable, and production-grade code.
    • English proficiency at an upper-intermediate level or higher.


    Nice-to-Have Skills:

    • Experience in building and deploying recommendation systems.
    • Familiarity with testing and MLOps practices.
    • A Master’s degree in Computer Science, or a related field.


    Benefits:

    • Education budget of $600 per year provided
    • Professional English courses
    • Medical Insurance


    Interview process:

    1. Recruiting Interview β€” (45 mins)
    2. Tech + Live Coding (60 mins)
    3. ML Design + Behavioral (60 mins)
    4. Cultural Fit interview β€” (60 mins)


    Thanks for your interest! In the case of your application, we will review it within 5 working days. If it meets the job requirements, we will arrange a call and will be happy to get to know each other better. Otherwise, we’d love to stay in touch waiting for other opportunities to become available.

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  • Β· 40 views Β· 4 applications Β· 29d

    AI Data Architect – Agentic AI Platform for BFSI

    Full Remote Β· Countries of Europe or Ukraine Β· 3 years of experience Β· Upper-Intermediate
    We're seeking a talented Data Architect to join our innovative startup, developing Guppy (GenAI Unified Platform for Performance and Yield)β€”a groundbreaking platform designed specifically for Banking and Financial Services (BFSI) software engineering. At...

    We're seeking a talented Data Architect to join our innovative startup, developing Guppy (GenAI Unified Platform for Performance and Yield)β€”a groundbreaking platform designed specifically for Banking and Financial Services (BFSI) software engineering.

    At Guppy, we leverage cutting-edge Agentic AI to significantly improve software development and deployment processes. Our platform meets the rigorous security, compliance, and performance standards demanded by regulated financial environments, offering AI-powered agents specialized in:

    • Business Analyst Agents: managing requirements, documentation, and analysis.
    • PMO Agents: optimizing project governance, coordination, and operational excellence.

    We're growing fast, and now we're looking for an experienced Data Architect with deep AI expertise to join our core team, shaping Guppy's foundational data infrastructure and agent memory frameworks.

    🎯 Your Mission at Guppy

    You'll play a pivotal role in designing and implementing data infrastructure tailored for BFSI software engineering needs. You’ll directly collaborate with our developers to:

    • Architect and integrate scalable data solutions within the Eliza AI framework.
    • Develop sophisticated vector embedding systems for semantic knowledge management.
    • Design multi-modal memory structures supporting episodic and semantic AI agent memory.
    • Create efficient Retrieval-Augmented Generation (RAG) pipelines integrated with vector databases.
    • Build advanced knowledge graph structures to track and link project entities and artifacts.
    • Implement secure data partitions compliant with stringent financial industry standards.
    • Develop APIs enabling seamless bidirectional integrations with enterprise tools (e.g., JIRA, Project Server).
    • Establish robust observability systems for continuous monitoring of AI memory and retrieval performance.

    πŸ› οΈ Technical Skills Required

    • Solid expertise with the Eliza framework and agent coordination functionalities.
    • Proven hands-on experience with vector databases (e.g., Pinecone, Weaviate, Milvus, Chroma).
    • Practical knowledge of embedding models (OpenAI, Cohere, or similar open-source alternatives).
    • Deep understanding of LangChain/LlamaIndex for AI agent memory and integration.
    • Demonstrated experience in developing and scaling knowledge graph architectures.
    • Strong proficiency in building semantic search systems and efficient RAG architectures.
    • Experience managing Model Control Plane (MCP) for orchestration of LLMs and enterprise integrations.
    • Advanced skills in Python, including async programming patterns and API design.

    🌟 What You Bring (Soft Skills)

    • Ability to thrive and deliver in a dynamic, fast-paced startup environment.
    • Strong analytical thinking and comfort tackling complex technical challenges.
    • Excellent communication skills, capable of clearly articulating complex solutions to diverse stakeholders.
    • Comfortable directly collaborating with founders and cross-functional teams.

    πŸŽ–οΈ Why Join Guppy?

    • Cutting-edge technology: Contribute to a sophisticated AI platform with real-world BFSI impact.
    • Innovative environment: Engage in rapid iteration cycles and direct founder collaboration.
    • Impact and ownership: Your contributions will directly shape our strategic growth and technical direction.
    • Growth Potential: High likelihood of continued involvement and professional advancement.
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  • Β· 30 views Β· 1 application Β· 24d

    Senior Machine Learning Ops Engineer

    Full Remote Β· Ukraine, Poland Β· 3.5 years of experience Β· Upper-Intermediate
    Description Who is our client: Our client is a global data products and technology company. They are on a mission to transform marketing by building the fastest, most connected data platform that bridges marketing strategy to scaled activation. They work...

    Description

    Who is our client:
    Our client is a global data products and technology company. They are on a mission to transform marketing by building the fastest, most connected data platform that bridges marketing strategy to scaled activation.
    They work with agencies and clients to transform the value of data by bringing together technology, data and analytics capabilities. Delivering this through the AI-enabled media and data platform for the next era of advertising.
    The client is endlessly curious. Their team of thinkers, builders, creators and problem solvers are over 1,000 strong, across 20 markets around the world. Our client’s culture is based on mutual trust, sharing, building, and learning together. They value simplicity, maintainability, automation, and metrics.

     

    About this role:
    Client’s team consists of 100+ engineers, designers, data scientists, implementation, and product people, working in small inter-disciplinary teams closely with creative agencies, media agencies, and with our customers, to develop and scale our leading digital advertising optimization suite that delivers amazing outcomes for brands and audiences.
    Client’s platforms are built with Python, React, and Clojure, are deployed using CI/CD, heavily exploit automation, and run on AWS, GCP, k8s, Snowflake, BigQuery, and more. They serve 9 petabytes and 77 billion objects annually, optimize thousands of campaigns to maximise ROI, and deliver 20 billion ad impressions across the globe. You’ll play a leading role in significantly scaling this further.
    As client’s first Machine Learning Operations (MLOps) Engineer on the team, you will play a pivotal role in bridging the gap between platform engineering, data science, and software engineering, building systems that drive the deployment, monitoring, and scalability of machine learning models. You will design and implement pipelines, automate workflows, and optimise model performance in training and production environments. You’ll lead the creation of process, implementation of tools, and creation of solutions mature how we integrate machine learning solutions into our production systems, while maintaining reliability, security, and efficiency. You’ll additionally play a leading role in driving continuous improvement in model lifecycle management, from development to deployment and monitoring.

     

    Requirements

    Technical Skills:
    β€’ Proficiency in Python for ML development; familiarity with additional languages like Clojure is a plus.
    β€’ Expertise in cloud platforms (AWS, GCP) and data warehouses like Snowflake or BigQuery.
    β€’ Strong knowledge of MLOps frameworks (e.g., Kubeflow, MLflow) and DevOps tools (e.g., Jenkins, GitLab, Flux)
    β€’ Experience with containerization (Docker) and orchestration (Kubernetes)
    β€’ Experience with infrastructure-as-code tools like Terraform
    Machine Learning Knowledge:
    β€’ Solid understanding of machine learning principles, including model evaluation, explainability, and retraining workflows.
    β€’ Hands-on experience with ML frameworks such as TensorFlow or PyTorch
    Big Data Handling:
    β€’ Proficiency in SQL/NoSQL databases and distributed computing systems like Dataprov, EMR, Spark, Hadoop
    Soft Skills:
    β€’ Strong communication skills to collaborate across multidisciplinary teams.
    β€’ Problem-solving mindset with the ability to work in agile environments
    Experience:
    β€’ At least 4+ years in platform, software, or MLOps engineering roles
    β€’ Proven track record of deploying scalable ML solutions in production environments

     

    Job responsibilities

    Model Deployment and Operations:
    β€’ Deploy, monitor, and maintain machine learning models in production environments.
    β€’ Automate model training, retraining, versioning, and governance processes.
    β€’ Monitor model performance, detect drift, and ensure scalability and reliability of ML workflows
    Infrastructure and Pipeline Management:
    β€’ Design and implement scalable MLOps pipelines for data ingestion, transformation, and model deployment.
    β€’ Build infrastructure-as-code solutions using tools like Terraform to manage cloud environments (AWS, GCP)
    Collaboration with Teams:
    β€’ Work closely with data scientists to operationalize machine learning models.
    β€’ Collaborate with software engineers to integrate ML systems into broader platforms
    Cloud and Big Data Expertise:
    β€’ Utilize cloud services from AWS, GCP, and Snowflake for scalable data storage and processing.
    DevOps Integration:
    β€’ Implement CI/CD pipelines and automations to streamline ML model deployment.
    β€’ Use containerization tools like Docker and orchestration platforms like Kubernetes for scalable deployments
    β€’ Use Observability platforms to monitor pipeline and operational health of model production, delivery and execution

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  • Β· 54 views Β· 14 applications Β· 16d

    Senior Parsing and Data Extraction Engineer

    Full Remote Β· Worldwide Β· 3 years of experience
    Altss is the fastest-growing, AI-driven investor intelligence platform for alternative asset classes. We extract and structure data on LPs, funds, deals, and key people globally, at a scale and depth unmatched in the industry. What You'll Do Build...

    Altss is the fastest-growing, AI-driven investor intelligence platform for alternative asset classes. We extract and structure data on LPs, funds, deals, and key people globally, at a scale and depth unmatched in the industry.

     

    What You'll Do

    • Build advanced parsers for large-scale, real-time data extraction from diverse sources: websites, PDFs, filings, news, databases, LinkedIn, and more.
    • Architect robust, resilient scraping systems capable of bypassing sophisticated anti-bot and geo-blocking measures.
    • Develop and deploy entity resolution algorithms to link extracted data across sources (e.g., people, firms, deals).
    • Leverage OSINT methodologies to uncover β€œhidden” data and extract insights not available via standard APIs or databases.
    • Collaborate with LLM/NLP engineers to automate structuring, cleaning, and validation of parsed data at scale.
    • Continuously monitor, QA, and improve pipelines for speed, accuracy, and reliability.
    • Mentor and lead junior team members (if desired), helping set best practices and high engineering standards.

       

    Who You Are

    • Proven experience building industrial-grade parsing/scraping infrastructureβ€”handling millions of records and high data velocity.
    • Expert in Python (Scrapy, Playwright, Selenium, Requests, BeautifulSoup, etc.), or similar modern scraping stacks.
    • Hands-on with headless browsers, proxies, captcha-solving, geo-rotation, and anti-bot techniques.
    • Deep understanding of HTML/XML/JSON structure, regex, and automated data cleaning.
    • Experience with data lakes/warehousing (PostgreSQL, ClickHouse, or similar), and orchestrating ETL/ELT pipelines.
    • Knowledge of OSINT, data enrichment, and cross-entity resolution a major plus.
    • Familiar with LLM/NLP workflows for data extraction/normalization is a strong plus.
    • Highly autonomous, outcome-oriented, and able to move fast in a lean, globally distributed team.

       

    Bonus Points For

    • Prior work on investor, finance, or B2B datasets.
    • Contributions to open-source scraping, data extraction, or OSINT tools.
    • Strong background in security, privacy, or compliance in data collection.
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  • Β· 105 views Β· 3 applications Β· 4d

    Machine Learning Engineer / Computer Vision

    Full Remote Β· Countries of Europe or Ukraine Β· 3 years of experience Β· Upper-Intermediate
    AIMPROSOFT β€” Machine Learning Engineer Opportunity! Aimprosoft, a fast-growing outsourcing IT company, is expanding its staff and is looking to hire a Middle Machine Learning Engineer to work on AI SDLC and company’s projects. About the role: ...


    πŸš€AIMPROSOFT β€”  Machine Learning Engineer Opportunity!  

     
    Aimprosoft, a fast-growing outsourcing IT company, is expanding its staff and is looking to hire a Middle Machine Learning Engineer to work on AI SDLC and company’s projects.  

     

    🎯About the role:  

     

    In this role, you will be responsible for contribute to the company’s AI SDLC initiatives, integration of AI tools, and delivery of internal knowledge-sharing sessions. The role involves hands-on work with Computer Vision and AI Agent systems (RAG pipelines), as well as participation in client projects on an outsourced basis. The ideal candidate brings a strong product mindset, is proactive in adopting and implementing state-of-the-art AI technologies, and is keen to mentor others and promote a culture of continuous learning and technical excellence. 
     
    πŸ”₯What We Need From You: 

    • 3+ years as a Machine Learning Engineer, Data Scientist or AI Engineer
    • Π•xperience training and deploying Computer Vision models
    • Proficient in Python
    • Extensive experience with PyTorch, OpenCV, PIL/Pillow, and torchvision
    • Proven ability to train, fine-tune, and optimize neural networks on large-scale image datasets
    • Experience with model optimization techniques (ONNX conversion, quantization, pruning)
    • Proactive in sharing knowledge and fostering a culture of learning
    • English proficiency at B2 (Upper-Intermediate) level or higher.

       

    AI Agents & RAG Systems:

    • Practical experience building and deploying Retrieval-Augmented Generation (RAG) systems
    • Proficiency with vector databases and embedding techniques (Qdrant, Milvus)
    • Strong knowledge of Large Language Models (LLMs) integration and tuning
    • Hands-on experience with LangChain, Haystack, LlamaIndex, or similar agent frameworks
    • Knowledge of prompt engineering and chain-of-thought reasoning techniques

       

    Infrastructure & Deployment:

    • Proficiency with Flask/FastAPI for ML model serving and API development
    • Hands-on experience with Docker for containerization
    • Proficient in Git for version control

       

    Nice to Have:

    • Experience with Transformers library and Hugging Face ecosystem
    • Knowledge of multimodal AI systems combining vision and language models
    • Familiarity with advanced RAG techniques (hybrid search, re-ranking, query expansion)
    • Experience with agent memory systems and persistent context management
    • Familiarity with MLOps tools (MLflow, Weights & Biases)
    • Familiarity with model serving frameworks (TorchServe, BentoML, vLLM)
    • Experience deploying ML models and applications on AWS infrastructure.

     

    πŸ’ΌWhat We Offer: 

    • Opportunity to work with AI 
    • A competitive salary that appreciates your skills and experience 
    • Cozy atmosphere and modern approaches. We have neither bureaucracy nor strict management or "working under pressure" conditions 
    • Opportunity to implement your ideas, tools, and approaches. We are open to changes and suggestions aimed at improvement 

       

     

     

     

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  • Β· 35 views Β· 1 application Β· 5d

    ML / Computer Vision Engineer (Human Understanding)

    Ukraine Β· Product Β· 3 years of experience Β· Intermediate
    Samsung R&D Institute Ukraine (SRUKR) is looking for ML / Computer Vision engineer who wants to apply theoretical knowledge and practical skills to participate in solving Human Understanding challenges in rapidly evolving Vision AI domain. The position...

    Samsung R&D Institute Ukraine (SRUKR) is looking for ML / Computer Vision engineer who wants to apply theoretical knowledge and practical skills to participate in solving Human Understanding challenges in rapidly evolving Vision AI domain. The position will involve different aspects of R&D including – research, analysis, prototyping, development and commercialization support of the innovative technologies. Resulting solutions are targeted on Samsung products and services reaching millions of users worldwide.

     

    Required skills / expertise:
     

    • Bachelor's (or higher) degree in computer science, math, statistics, or related field
    • 3+ years of experience in conventional and ML/DL based image processing and computer vision
    • Practical experience in custom NN-architecture development, training and evaluation
    • Strong theoretical knowledge and practical skills in computer vision algorithms (OpenCV)
    • Solid Python programming skills (numpy, pandas, matplotlib)
    • Knowledge in linear algebra, probability, optimization, and 3D geometry
    • Proficiency in math, algorithms and data structures
    • Experience with object-oriented design and development
    • Basic C++ knowledge
    • Understanding research methodologies and S/W development lifecycle

     

    Would be a plus:
     

    • Experience in 3D face reconstruction and face attributes detection
    • Experience with ComfyUI and data generation activities
    • Participation in CV/ML/DL-intensive research (papers, competitions, patents, etc…)
    • Pet projects portfolio that includes – object detection/recognition/tracking, key-points detection and tracking, semantic/instance segmentation, etc.
    • Experience with vision transformer, vision encoder-decoder architectures
    • Experience with model optimizations for on-device inference (ONNX-runtime, TFLite, SNPE)
    • Experience with CPU/GPU profiling tools
    • Cross-cultural experience and working English to feel confident in the international team

     

    Key Responsibilities:
     

    • R&D activities in CV based Human Understanding domain (person/face attributes detection, recognition and tracking, 3D face reconstruction).
    • Design NN-based solutions and train required ML/DL models
    • Optimize algorithms & ML/DL models / their inference and size
    • Transfer models and solutions to the edge devices using appropriate frameworks (ONNX, TFLite, SNPE, etc)
    • Participate in design process of system architecture
    • Collaborate with other R&D engineers worldwide to improve product quality with the latest industry trends in relevant technologies
    • Maintain and support existing solutions and services
    • Develop demo applications for various platforms
    • Opportunity to participate in publication and patent activities

     

    Working Conditions:
     

    • GIG contract
    • remote work is possible as well as work in Kyiv office
       

    Benefits:
     

    • competitive salary, annual salary review, annual bonuses
    • paid 28 work days of annual vacations and sick leaves
    • opportunity to become an inventor of international patents with paid bonuses
    • medical & life insurance for employees and their childrens
    • paid lunches
    • discounts to Samsung products, services
    • regular education and self-development on internal courses and seminars
    • hybrid work format, working in office is required for some tasks
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  • Β· 26 views Β· 3 applications Β· 5d

    Data Scientist

    Full Remote Β· Ukraine Β· 3 years of experience Β· Intermediate
    Π‘Ρ‚Π°Π½ΡŒΡ‚Π΅ Ρ‡Π°ΡΡ‚ΠΈΠ½ΠΎΡŽ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ, Ρ‰ΠΎ ΡΡ‚Π²ΠΎΡ€ΡŽΡ” Ρ†ΠΈΡ„Ρ€ΠΎΠ²Ρƒ Ρ€Π΅Π°Π»ΡŒΠ½Ρ–ΡΡ‚ΡŒ! MODUS X β€” ΡƒΠΊΡ€Π°Ρ—Π½ΡΡŒΠΊΠ° Π†Π’-компанія, ΠΊΠΎΠΌΠ°Π½Π΄Π° 650+ Ρ–Π½ΠΆΠ΅Π½Π΅Ρ€Ρ–Π², Π°Ρ€Ρ…Ρ–Ρ‚Π΅ΠΊΡ‚ΠΎΡ€Ρ–Π², спСціалістів Π· Π±Π΅Π·ΠΏΠ΅ΠΊΠΈ Ρ‚Π° датасаєнтистів.​ Ми Ρ€ΠΎΠ·ΠΏΠΎΡ‡Π°Π»ΠΈ Ρ‚Π° ΠΏΡ€ΠΎΠ΄ΠΎΠ²ΠΆΡƒΡ”ΠΌΠΎ супровід Ρ†ΠΈΡ„Ρ€ΠΎΠ²ΠΎΡ— трансформації Π”Π’Π•Πš, яка ΠΏΠ΅Ρ€ΡˆΠΎΡŽ Π²...

    Π‘Ρ‚Π°Π½ΡŒΡ‚Π΅ Ρ‡Π°ΡΡ‚ΠΈΠ½ΠΎΡŽ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ, Ρ‰ΠΎ ΡΡ‚Π²ΠΎΡ€ΡŽΡ” Ρ†ΠΈΡ„Ρ€ΠΎΠ²Ρƒ Ρ€Π΅Π°Π»ΡŒΠ½Ρ–ΡΡ‚ΡŒ!

     

    MODUS X β€” ΡƒΠΊΡ€Π°Ρ—Π½ΡΡŒΠΊΠ° Π†Π’-компанія, ΠΊΠΎΠΌΠ°Π½Π΄Π° 650+ Ρ–Π½ΠΆΠ΅Π½Π΅Ρ€Ρ–Π², Π°Ρ€Ρ…Ρ–Ρ‚Π΅ΠΊΡ‚ΠΎΡ€Ρ–Π², спСціалістів Π· Π±Π΅Π·ΠΏΠ΅ΠΊΠΈ Ρ‚Π° Π΄Π°Ρ‚асаєнтистів.​ Ми Ρ€ΠΎΠ·ΠΏΠΎΡ‡Π°Π»ΠΈ Ρ‚Π° ΠΏΡ€ΠΎΠ΄ΠΎΠ²ΠΆΡƒΡ”ΠΌΠΎ супровід Ρ†ΠΈΡ„Ρ€ΠΎΠ²ΠΎΡ— трансформації Π”Π’Π•Πš, яка ΠΏΠ΅Ρ€ΡˆΠΎΡŽ Π² Π΅Π½Π΅Ρ€Π³Π΅Ρ‚ΠΈΡ†Ρ– Π£ΠΊΡ€Π°Ρ—Π½ΠΈ стала Π½Π° ΡˆΠ»ΡΡ… ΠΌΠ°ΡΡˆΡ‚Π°Π±Π½ΠΎΠ³ΠΎ Π΄Ρ–Π΄ΠΆΠΈΡ‚Π°Π»-пСрСтворСння. Нині Π²ΠΈΠ΄Ρ–Π»ΠΈΠ»ΠΈΡΡŒ Π² ΠΎΠΊΡ€Π΅ΠΌΡƒ ΠΊΠΎΠΌΠΏΠ°Π½Ρ–ΡŽ, Ρ‰ΠΎΠ±ΠΈ ділитися своїм досвідом Ρ‚Π° Π΅ΠΊΡΠΏΠ΅Ρ€Ρ‚ΠΈΠ·ΠΎΡŽ Π½Π°Π·ΠΎΠ²Π½Ρ–, Π·Π°Π»ΠΈΡˆΠ°ΡŽΡ‡ΠΈΡΡŒ Π†Π’-ΠΎΠΏΠΎΡ€ΠΎΡŽ для Ρ‚ΠΈΡ…, Ρ…Ρ‚ΠΎ нСсС світло Ρ‚Π° ΡΠΏΡ€ΠΈΡΡ” Π²Ρ–Π΄Π½ΠΎΠ²Π»Π΅Π½Π½ΡŽ ΠΊΡ€Π°Ρ—Π½ΠΈ.

    Π¨ΡƒΠΊΠ°Ρ”ΠΌΠΎ Middle Data ScientistΡ–st, для підсилСння Data Science-ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ. Π―ΠΊΠΈΠΉ Π±ΡƒΠ΄Π΅ Π΄ΠΎΠ»ΡƒΡ‡Π΅Π½ΠΈΠΉ Π΄ΠΎ Π²ΠΈΠΊΠΎΠ½Π°Π½Π½Ρ ΠΏΠΎΠ²Π½ΠΎΠ³ΠΎ Ρ†ΠΈΠΊΠ»Ρƒ ΠΏΡ€ΠΎΠ΅ΠΊΡ‚Ρ–Π² β€” Π²Ρ–Π΄ Π°Π½Π°Π»Ρ–Π·Ρƒ Π΄Π°Π½ΠΈΡ… Π΄ΠΎ Π·Π°ΠΏΡƒΡΠΊΡƒ ΠΌΠΎΠ΄Π΅Π»Ρ– Ρƒ ΠΏΡ€ΠΎΠ΄Π°ΠΊΡˆΠ½, ΠΏΡ€Π°Ρ†ΡŽΡŽΡ‡ΠΈ Ρƒ ΠΊΡ€ΠΎΡ-Ρ„ΡƒΠ½ΠΊΡ†Ρ–ΠΎΠ½Π°Π»ΡŒΠ½Ρ–ΠΉ ΠΊΠΎΠΌΠ°Π½Π΄Ρ–.

     

    Π€ΡƒΠ½ΠΊΡ†Ρ–Ρ— посади:

    • Аналіз ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌΠΈ Ρ‚Π° ΠΏΠΎΡΡ‚Π°Π½ΠΎΠ²ΠΊΠ° Π·Π°Π΄Π°Ρ‡Ρ–
    • Π—Π±Ρ–Ρ€, очищСння Ρ‚Π° ΠΏΡ–Π΄Π³ΠΎΡ‚ΠΎΠ²ΠΊΠ° Π΄Π°Π½ΠΈΡ…
    • МодСлювання Ρ‚Π° Π΅ΠΊΡΠΏΠ΅Ρ€ΠΈΠΌΠ΅Π½Ρ‚ΠΈ
    • Валідація Ρ‚Π° ΠΏΠΎΡΡΠ½Π΅Π½Π½Ρ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ–Π²
    • Бпівпраця Ρ‚Π° ΠΊΠΎΠΌΡƒΠ½Ρ–кація
    • ΠŸΠΎΠ»Ρ–ΠΏΡˆΠ΅Π½Π½Ρ процСсів Ρ‚Π° ΠΌΠ΅Π½Ρ‚орство
    • R&D Ρ‚Π° Ρ€ΠΎΠ·Π²ΠΈΡ‚ΠΎΠΊ СкспСртизи

     

    ΠŸΡ€ΠΎΡ„Π΅ΡΡ–ΠΉΠ½Ρ– ΠΊΠΎΠΌΠΏΠ΅Ρ‚Π΅Π½Ρ†Ρ–Ρ—:

    • Вміння Ρ‡Ρ–Ρ‚ΠΊΠΎ Ρ„ΠΎΡ€ΠΌΡƒΠ»ΡŽΠ²Π°Ρ‚ΠΈ Π·Π°Π΄Π°Ρ‡Ρƒ Ρ‚Π° ΡΡ‚Π°Π²ΠΈΡ‚ΠΈ питання
    • Вміння ΠΏΠΎΠ΄ΠΈΠ²ΠΈΡ‚ΠΈΡΡŒ Π½Π° ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌΡƒ ΠΏΡ–Π΄ Ρ–Π½ΡˆΠΈΠΌ ΠΊΡƒΡ‚ΠΎΠΌ Π·ΠΎΡ€Ρƒ
    • Python (pandas, NumPy, scikit-learn), SQL; Π²ΠΏΠ΅Π²Π½Π΅Π½Π° Ρ€ΠΎΠ±ΠΎΡ‚Π° Π· Git.
    • ΠšΠ»Π°ΡΠΈΡ‡Π½Ρ– ML-Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠΈ (Gradient Boosting β€” XGBoost/LightGBM/CatBoost, Random Forest, Logistic/Linear Regression, k-NN); знання ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ–Π² рСгуляризації, крос-Π²Π°Π»Ρ–Π΄Π°Ρ†Ρ–Ρ— Ρ‚Π° ΠΏΡ–Π΄Π±ΠΎΡ€Ρƒ Π³Ρ–ΠΏΠ΅Ρ€ΠΏΠ°Ρ€Π°ΠΌΠ΅Ρ‚Ρ€Ρ–Π².
    • Ймовірнісні Ρ€ΠΎΠ·ΠΏΠΎΠ΄Ρ–Π»ΠΈ, ΠΏΠ΅Ρ€Π΅Π²Ρ–Ρ€ΠΊΠ° Π³Ρ–ΠΏΠΎΡ‚Π΅Π·, A/B-тСсти, Ρ–Π½Ρ‚Π΅ΠΏΡ€Π΅Ρ‚ΠΎΠ²Π°Π½Ρ–ΡΡ‚ΡŒ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ.
    • PyTorch Π°Π±ΠΎ TensorFlow/Keras для Π·Π°Π΄Π°Ρ‡ CV Ρ‡ΠΈ NLP; уміння Π±ΡƒΠ΄ΡƒΠ²Π°Ρ‚ΠΈ Ρ‚Π° Ρ‚Ρ€Π΅Π½ΡƒΠ²Π°Ρ‚ΠΈ ΠΌΠΎΠ΄Π΅Π»Ρ– Π· TensorBoard-логуванням.
    • MLflow / Weights & Biases, Docker; Π±Π°Π·ΠΎΠ²Π΅ розуміння CI/CD для ML-ΠΏΠ°ΠΉΠΏΠ»Π°ΠΉΠ½Ρ–Π².
    • ΠŸΡ€Π°ΠΊΡ‚ΠΈΡ‡Π½ΠΈΠΉ досвід Ρƒ Ρ…ΠΎΡ‡Π° Π± ΠΎΠ΄Π½Ρ–ΠΉ Ρ–Π· ΠΏΠ»Π°Ρ‚Ρ„ΠΎΡ€ΠΌ (AWS, GCP, Azure) для розгортання Π°Π±ΠΎ трСнування ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ.
    • ΠΠ°ΡΠ²Π½Ρ–ΡΡ‚ΡŒ сСртифікації ΠΏΠΎ Data&AI
    • Вміння Π½Π΅Π·Π°Π»Π΅ΠΆΠ½ΠΎ пСрСвіряти Π²Ρ…Ρ–Π΄Π½Ρ– Π΄Π°Π½Ρ– Ρ‚Π° Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚
    • ΠΠ²Ρ‚ΠΎΠ½ΠΎΠΌΠ½Ρ–ΡΡ‚ΡŒ
    • ΠšΠΎΠΌΡƒΠ½Ρ–ΠΊΠ°Π±Π΅Π»ΡŒΠ½Ρ–ΡΡ‚ΡŒ

     

    Ми ΠΏΡ€ΠΎΠΏΠΎΠ½ΡƒΡ”ΠΌΠΎ:

    • ΠžΡ„Ρ–Ρ†Ρ–ΠΉΠ½Π΅ ΠΏΡ€Π°Ρ†Π΅Π²Π»Π°ΡˆΡ‚ΡƒΠ²Π°Π½Π½Ρ
    • KΠΎΠ½ΠΊΡƒΡ€Π΅Π½Ρ‚Π½ΠΈΠΉ Ρ€Ρ–Π²Π΅Π½ΡŒ Π·Π°Ρ€ΠΎΠ±Ρ–Ρ‚Π½ΠΎΡ— ΠΏΠ»Π°Ρ‚ΠΈ Ρ‚Π° ΡΠΎΡ†Ρ–Π°Π»ΡŒΠ½Ρ– Π³Π°Ρ€Π°Π½Ρ‚Ρ–Ρ—
    • ΠšΠΎΡ€ΠΏΠΎΡ€Π°Ρ‚ΠΈΠ²Π½Π° ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠ° ΠΌΠ΅Π΄ΠΈΡ‡Π½ΠΎΠ³ΠΎ страхування Ρ‚Π° ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠ° психологічної ΠΏΡ–Π΄Ρ‚Ρ€ΠΈΠΌΠΊΠΈ співробітників
    • Π ΠΎΠ±ΠΎΡ‚Ρƒ Π² Ρ–Π½Π½ΠΎΠ²Π°Ρ†Ρ–ΠΉΠ½ΠΎΠΌΡƒ ΠΏΠ°Ρ€ΠΊΡƒ Unit City
    • ΠœΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡ‚Ρ– навчання Ρ‚Π° ΠΏΡ€ΠΎΡ„Ссійний Ρ€ΠΎΠ·Π²ΠΈΡ‚ΠΎΠΊ (ΠΎΠ½Π»Π°ΠΉΠ½ курси, Π°ΡƒΠ΄ΠΈΡ‚ΠΎΡ€Π½Ρ– Ρ‚Ρ€Π΅Π½Ρ–Π½Π³ΠΈ, майстСр-класи, профСсійні ΡΠΏΡ–Π»ΡŒΠ½ΠΎΡ‚ΠΈ)

     

    Ми Ρ†Ρ–Π½ΡƒΡ”ΠΌΠΎ ваш інтСрСс Π΄ΠΎ MODUS X Ρ‚Π° Π³ΠΎΡ‚ΠΎΠ²Π½Ρ–ΡΡ‚ΡŒ ΠΏΡ€ΠΈΠΉΠΌΠ°Ρ‚ΠΈ Π²ΠΈΠΊΠ»ΠΈΠΊΠΈ. Π’ΡƒΡ‚ ΠΊΠΎΠΆΠ΅Π½ ΠΌΠΎΠΆΠ΅ Ρ€ΠΎΠ·ΠΊΡ€ΠΈΡ‚ΠΈ свої Ρ‚Π°Π»Π°Π½Ρ‚ΠΈ ΠΉ Π·Ρ€ΠΎΠ±ΠΈΡ‚ΠΈ внСсок Ρƒ ΡΠΏΡ–Π»ΡŒΠ½ΠΈΠΉ успіх. Ми Ρ–нвСстуємо Π² Ρ€ΠΎΠ·Π²ΠΈΡ‚ΠΎΠΊ, Π΄ΠΎΠΏΠΎΠΌΠ°Π³Π°Ρ”ΠΌΠΎ ΠΎΡ‚Ρ€ΠΈΠΌΡƒΠ²Π°Ρ‚ΠΈ Π½ΠΎΠ²Ρ– знання Ρ‚Π° Π΄ΠΎΡΡΠ³Π°Ρ‚ΠΈ профСсійних Ρ†Ρ–Π»Π΅ΠΉ.

     

    Наша ΠΊΠΎΠΌΠ°Π½Π΄Π° ΡƒΠ²Π°ΠΆΠ½ΠΎ розглядає всі заявки, Ρ– ΡΠΊΡ‰ΠΎ ваша ΠΊΠ°Π½Π΄ΠΈΠ΄Π°Ρ‚ΡƒΡ€Π° Π²Ρ–Π΄ΠΏΠΎΠ²Ρ–Π΄Π°Ρ” Π²ΠΈΠΌΠΎΠ³Π°ΠΌ вакансії, Ρ€Π΅ΠΊΡ€ΡƒΡ‚Π΅Ρ€ обов’язково Π·Π²β€™ΡΠΆΠ΅Ρ‚ΡŒΡΡ Π· Π²Π°ΠΌΠΈ Π²ΠΏΡ€ΠΎΠ΄ΠΎΠ²ΠΆ 2 Ρ‚ΠΈΠΆΠ½Ρ–Π².

     

    Π‘Ρ–Π»ΡŒΡˆΠ΅ Ρ–Π½Ρ„ΠΎΡ€ΠΌΠ°Ρ†Ρ–Ρ— ΠΏΡ€ΠΎ ΠΊΠΎΠΌΠΏΠ°Π½Ρ–ΡŽ Ρ‚Π° Π½Π°Ρˆ досвід Π½Π° ΠΎΡ„Ρ–Ρ†Ρ–ΠΉΠ½Ρ–ΠΉ сторінці MODUS X Π² LinkedIn.

     

    ΠΠ°ΠΏΡ€Π°Π²Π»ΡΡŽΡ‡ΠΈ Ρ€Π΅Π·ΡŽΠΌΠ΅ Π½Π° Ρ†ΡŽ Π²Π°ΠΊΠ°Π½ΡΡ–ΡŽ, Π’ΠΈ Π½Π°Π΄Π°Ρ”Ρ‚Π΅ Π·Π³ΠΎΠ΄Ρƒ Π’ΠžΠ’ Β«ΠœΠžΠ”Π£Π‘ Π†ΠšΠ‘Β» Π½Π° ΠΎΠ±Ρ€ΠΎΠ±ΠΊΡƒ Π½Π°Π΄Π°Π½ΠΈΡ… Π’Π°ΠΌΠΈ ΠΏΠ΅Ρ€ΡΠΎΠ½Π°Π»ΡŒΠ½ΠΈΡ… Π΄Π°Π½ΠΈΡ… Π·Π³Ρ–Π΄Π½ΠΎ Π—Π°ΠΊΠΎΠ½Ρƒ Π£ΠΊΡ€Π°Ρ—Π½ΠΈ Β«ΠŸΡ€ΠΎ захист ΠΏΠ΅Ρ€ΡΠΎΠ½Π°Π»ΡŒΠ½ΠΈΡ… Π΄Π°Π½ΠΈΡ…Β». Π—Π³ΠΎΠ΄Π° Π½Π°Π΄Π°Ρ”Ρ‚ΡŒΡΡ Π² Ρ‚ΠΎΠΌΡƒ числі для Ρ—Ρ… ΠΎΠ±Ρ€ΠΎΠ±ΠΊΠΈ Π² Π·ΠΎΠ²Π½Ρ–ΡˆΠ½Ρ–Ρ… систСмах, Π· ΠΌΠ΅Ρ‚ΠΎΡŽ супроводТСння процСсу Π½Π°ΠΉΠΌΡƒ.

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  • Β· 45 views Β· 10 applications Β· 30d

    Data Science (Π ΠΈΠ·ΠΈΠΊ-ΠΌΠΎΠ΄Π΅Π»Ρ–, Π°Π½Ρ‚ΠΈΡ„Ρ€ΠΎΠ΄)

    Full Remote Β· Countries of Europe or Ukraine Β· Product Β· 3 years of experience Β· Beginner/Elementary
    Мова Ρ‚Π° Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³Ρ–Ρ— Python Π°Π±ΠΎ R Scikit-learn XGBoost LightGBM CatBoost TensorFlow SQL Π’Π²ΠΎΡ— обов’язки БтворСння ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ скорингу для ΠΎΡ†Ρ–Π½ΠΊΠΈ ΠΊΡ€Π΅Π΄ΠΈΡ‚Π½ΠΎΠ³ΠΎ Ρ€ΠΈΠ·ΠΈΠΊΡƒ (Π°ΠΏΠ»Ρ–ΠΊΠ°Ρ†Ρ–ΠΉΠ½ΠΈΠΉ, ΠΏΠΎΠ²Π΅Π΄Ρ–Π½ΠΊΠΎΠ²ΠΈΠΉ) Π ΠΎΠ·Ρ€ΠΎΠ±ΠΊΠ° Π°Π½Ρ‚ΠΈΡ„Ρ€ΠΎΠ΄-систСм для виявлСння ΠΏΡ–Π΄ΠΎΠ·Ρ€Ρ–Π»ΠΈΡ…...

    Мова Ρ‚Π° Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³Ρ–Ρ—

    Python Π°Π±ΠΎ R   Scikit-learn  XGBoost  LightGBM  CatBoost  TensorFlow  SQL

     

    Π’Π²ΠΎΡ— обов’язки

     

    БтворСння ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ скорингу для ΠΎΡ†Ρ–Π½ΠΊΠΈ ΠΊΡ€Π΅Π΄ΠΈΡ‚Π½ΠΎΠ³ΠΎ Ρ€ΠΈΠ·ΠΈΠΊΡƒ (Π°ΠΏΠ»Ρ–ΠΊΠ°Ρ†Ρ–ΠΉΠ½ΠΈΠΉ, ΠΏΠΎΠ²Π΅Π΄Ρ–Π½ΠΊΠΎΠ²ΠΈΠΉ)

    Π ΠΎΠ·Ρ€ΠΎΠ±ΠΊΠ° Π°Π½Ρ‚ΠΈΡ„Ρ€ΠΎΠ΄-систСм для виявлСння ΠΏΡ–Π΄ΠΎΠ·Ρ€Ρ–Π»ΠΈΡ… Ρ‚Ρ€Π°Π½Π·Π°ΠΊΡ†Ρ–ΠΉ Ρ‚Π° ΡˆΠ°Ρ…Ρ€Π°ΠΉΡΡ‚Π²Π°

    ВпровадТСння Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΡ–Π² Ρ€Π°Π½Π½ΡŒΠΎΠ³ΠΎ попСрСдТСння Ρ€ΠΈΠ·ΠΈΠΊΡ–Π² Π½Π° основі Π΄Π°Π½ΠΈΡ… Ρ‚Ρ€Π°Π½Π·Π°ΠΊΡ†Ρ–ΠΉ, ΠΏΠΎΠ²Π΅Π΄Ρ–Π½ΠΊΠΎΠ²ΠΈΡ… Ρ‚Π° Π΄Π΅ΠΌΠΎΠ³Ρ€Π°Ρ„Ρ–Ρ‡Π½ΠΈΡ… Π΄Π°Π½ΠΈΡ…

    ΠŸΡ–Π΄Π³ΠΎΡ‚ΠΎΠ²ΠΊΠ° Π²Π΅Π»ΠΈΠΊΠΈΡ… обсягів Π΄Π°Π½ΠΈΡ… для трСнування ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ (прСпроцСсинг, трансформація, очищСння)

    Аналіз Ρ‚Ρ€Π°Π½Π·Π°ΠΊΡ†Ρ–ΠΉΠ½ΠΈΡ… Π΄Π°Π½ΠΈΡ…, ΠΏΠΎΠ²Π΅Π΄Ρ–Π½ΠΊΠΎΠ²ΠΈΡ… ΠΏΠ°Ρ‚Π΅Ρ€Π½Ρ–Π² ΠΊΠ»Ρ–Ρ”Π½Ρ‚Ρ–Π² Ρ‚Π° створСння Π½ΠΎΠ²ΠΈΡ… Ρ„Ρ–Ρ‡ для ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ

    Використання історичних Π΄Π°Π½ΠΈΡ… для визначСння Ρ‚Ρ€Π΅Π½Π΄Ρ–Π² ΡˆΠ°Ρ…Ρ€Π°ΠΉΡΡ‚Π²Π° Π°Π±ΠΎ фінансових Ρ€ΠΈΠ·ΠΈΠΊΡ–Π²

    ΠŸΡ€ΠΎΠ²Π΅Π΄Π΅Π½Π½Ρ тСстування, ΠΎΡ†Ρ–Π½ΠΊΠΈ Ρ‚Π° ΠΎΠΏΡ‚ΠΈΠΌΡ–Π·Π°Ρ†Ρ–Ρ— ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π·Π° допомогою ΠΌΠ΅Ρ‚Ρ€ΠΈΠΊ точності, recall, precision, AUC-ROC, F1

    РСалізація Ρ‚Π° ΠΏΡ–Π΄Ρ‚Ρ€ΠΈΠΌΠΊΠ° ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Ρƒ Ρ€Π΅Π°Π»ΡŒΠ½ΠΎΠΌΡƒ часі для забСзпСчСння високої ΡˆΠ²ΠΈΠ΄ΠΊΠΎΡΡ‚Ρ– ΠΎΠ±Ρ€ΠΎΠ±ΠΊΠΈ Ρ‚Π° точності

    ІнтСграція ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Ρƒ ΠΏΡ€ΠΎΠ΄Π°ΠΊΡˆΠ½ сСрСдовищС

    ΠœΠΎΠ½Ρ–Ρ‚ΠΎΡ€ΠΈΠ½Π³ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π½Π° ΠΏΡ€ΠΎΠ΄Π°ΠΊΡˆΠ΅Π½Ρ–

    ΠœΠ°ΡΡˆΡ‚Π°Π±ΡƒΠ²Π°Π½Π½Ρ Ρ€Ρ–ΡˆΠ΅Π½ΡŒ для Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Π· Π²Π΅Π»ΠΈΠΊΠΈΠΌ обсягом Ρ‚Ρ€Π°Π½Π·Π°ΠΊΡ†Ρ–ΠΉ Ρƒ Ρ€Π΅Π°Π»ΡŒΠ½ΠΎΠΌΡƒ часі

    Π ΠΎΠ±ΠΎΡ‚Π° Π· Π°Π½Π°Π»Ρ–Ρ‚ΠΈΠΊΠ°ΠΌΠΈ Π΄Π°Π½ΠΈΡ…, ΠΏΡ€ΠΎΠ΄ΡƒΠΊΡ‚ΠΎΠ²ΠΈΠΌΠΈ ΠΊΠΎΠΌΠ°Π½Π΄Π°ΠΌΠΈ Ρ‚Π° Π΄Π΅ΠΏΠ°Ρ€Ρ‚Π°ΠΌΠ΅Π½Ρ‚ΠΎΠΌ Ρ€ΠΈΠ·ΠΈΠΊΡ–Π² для визначСння бізнСс-Π²ΠΈΠΌΠΎΠ³

    Взаємодія Π· Ρ–Π½ΠΆΠ΅Π½Π΅Ρ€Π°ΠΌΠΈ для Ρ–Π½Ρ‚Π΅Π³Ρ€Π°Ρ†Ρ–Ρ— ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Ρƒ Ρ–ΡΠ½ΡƒΡŽΡ‡Ρ– ΠΏΠ»Π°Ρ‚Ρ„ΠΎΡ€ΠΌΠΈ

     

    Π’ΠΈΠΌΠΎΠ³ΠΈ

     

    Π’ΠΈΡ‰Π° Ρ‚Π΅Ρ…Π½Ρ–Ρ‡Π½Π° освіта (ΠΊΠΎΠΌΠΏβ€™ΡŽΡ‚Π΅Ρ€Π½Ρ– Π½Π°ΡƒΠΊΠΈ, ΠΌΠ°Ρ‚Π΅ΠΌΠ°Ρ‚ΠΈΠΊΠ°, статистика, Π΅ΠΊΠΎΠ½ΠΎΠΌΡ–ΠΊΠ°, Π°Π±ΠΎ фінанси)

    ΠœΡ–Π½Ρ–ΠΌΡƒΠΌ 3 Ρ€ΠΎΠΊΠΈ досвіду Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Ρƒ сфСрі машинного навчання Ρ‚Π° Ρ€ΠΈΠ·ΠΈΠΊ-ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ

    ΠŸΡ€Π°ΠΊΡ‚ΠΈΡ‡Π½ΠΈΠΉ досвід Ρ€ΠΎΠ·Ρ€ΠΎΠ±ΠΊΠΈ скорингових ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π°Π±ΠΎ Π°Π½Ρ‚ΠΈΡ„Ρ€ΠΎΠ΄-систСм

    Високий Ρ€Ρ–Π²Π΅Π½ΡŒ володіння Python Π°Π±ΠΎ R

    ML-Ρ„Ρ€Π΅ΠΉΠΌΠ²ΠΎΡ€ΠΊΠΈ: Scikit-learn, XGBoost, LightGBM, CatBoost

    Π“Π»ΠΈΠ±ΠΎΠΊΠ΅ навчання: TensorFlow, PyTorch (Π΄ΠΎΠ΄Π°Ρ‚ΠΊΠΎΠ²ΠΎ)

    Досвід Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Π· SQL для отримання Π΄Π°Π½ΠΈΡ… Ρ–Π· Π±Π°Π·

    Π ΠΎΠ±ΠΎΡ‚Π° Π· Π²Π΅Π»ΠΈΠΊΠΈΠΌΠΈ Π΄Π°Π½ΠΈΠΌΠΈ: Spark (Π±ΡƒΠ΄Π΅ плюсом)

    РСгрСсії, Π΄Π΅Ρ€Π΅Π²Π° Ρ€Ρ–ΡˆΠ΅Π½ΡŒ, ансамблСві ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈ, кластСризація, аномалія Π΄Π΅Ρ‚Π΅ΠΊΡˆΠ½ (anomaly detection)

    ROC-AUC, Precision/Recall, Gini, KS

    ΠŸΠΎΠ±ΡƒΠ΄ΠΎΠ²Π° Π°Π½Ρ‚ΠΈΡ„Ρ€ΠΎΠ΄-ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π½Π° основі ΠΏΠΎΠ²Π΅Π΄Ρ–Π½ΠΊΠΎΠ²ΠΈΡ… Π΄Π°Π½ΠΈΡ… (Π½Π°ΠΏΡ€. ΠΌΠΎΠ΄Π΅Π»Ρ– виявлСння Π°Π½ΠΎΠΌΠ°Π»Ρ–ΠΉ)

    Досвід Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Π· часо-рядними Π΄Π°Π½ΠΈΠΌΠΈ Ρ‚Π° Ρ„Ρ–Ρ‡Π°ΠΌΠΈ для Π°Π½Π°Π»Ρ–Π·Ρƒ Ρ‚Ρ€Π°Π½Π·Π°ΠΊΡ†Ρ–ΠΉ

    Знання систСм скорингу 

    Досвід Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Π· API для Ρ€Π΅Π°Π»ΡŒΠ½ΠΎΠ³ΠΎ часу

    Знання Ρ…ΠΌΠ°Ρ€Π½ΠΈΡ… сСрвісів (AWS, Azure)

    БистСми ΠΊΠΎΠ½Ρ‚Ρ€ΠΎΠ»ΡŽ вСрсій: Git

     

    Π”ΠΎΠ±Ρ€Π΅ ΠΌΠ°Ρ‚ΠΈ

     

    Досвід Ρƒ створСнні rule-based Ρ‚Π° ML-Π±Π°Π·ΠΎΠ²Π°Π½ΠΈΡ… Π°Π½Ρ‚ΠΈΡ„Ρ€ΠΎΠ΄-систСм

    Розуміння бізнСс-Π»ΠΎΠ³Ρ–ΠΊΠΈ фінансових процСсів, крСдитування Ρ‚Π° ΠΏΠ»Π°Ρ‚Π΅ΠΆΡ–Π²

    Досвід Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Π· graph-based систСмами для Π΄Π΅Ρ‚Π΅ΠΊΡ†Ρ–Ρ— ΡˆΠ°Ρ…Ρ€Π°ΠΉΡΡ‚Π²Π°

    Досвід Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Π· систСмами ΠΏΠΎΡ‚ΠΎΠΊΠΎΠ²ΠΎΡ— ΠΎΠ±Ρ€ΠΎΠ±ΠΊΠΈ Π΄Π°Π½ΠΈΡ…

     

    More
  • Β· 48 views Β· 3 applications Β· 25d

    Data Scientist (NLP + Recommender Systems)

    Ukraine Β· Product Β· 3 years of experience Ukrainian Product πŸ‡ΊπŸ‡¦
    Команда MEGOGO ΡˆΡƒΠΊΠ°Ρ” Data Scientist, який Π΄ΠΎΠΏΠΎΠΌΠΎΠΆΠ΅ вдосконалити Π½Π°ΡˆΡ– систСми пСрсоналізації, ΠΏΠΎΡˆΡƒΠΊΡƒ Ρ‚Π° Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°Ρ†Ρ–ΠΉ. Π―ΠΊΡ‰ΠΎ Ρ‚ΠΎΠ±Ρ– Ρ†Ρ–ΠΊΠ°Π²ΠΎ ΠΏΡ€Π°Ρ†ΡŽΠ²Π°Ρ‚ΠΈ Π· Ρ€Π΅Π°Π»ΡŒΠ½ΠΈΠΌΠΈ Π΄Π°Π½ΠΈΠΌΠΈ ΠΌΡ–Π»ΡŒΠΉΠΎΠ½Ρ–Π² користувачів, застосовувати NLP-ΠΌΠΎΠ΄Π΅Π»Ρ– Π² ΠΏΡ€ΠΎΠ΄Π°ΠΊΡˆΠ΅Π½Ρ– Ρ‚Π° Ρ€ΠΎΠ·Π²ΠΈΠ²Π°Ρ‚ΠΈ сучасні...

    Команда MEGOGO ΡˆΡƒΠΊΠ°Ρ” Data Scientist, який Π΄ΠΎΠΏΠΎΠΌΠΎΠΆΠ΅ вдосконалити Π½Π°ΡˆΡ– систСми пСрсоналізації, ΠΏΠΎΡˆΡƒΠΊΡƒ Ρ‚Π° Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°Ρ†Ρ–ΠΉ. Π―ΠΊΡ‰ΠΎ Ρ‚ΠΎΠ±Ρ– Ρ†Ρ–ΠΊΠ°Π²ΠΎ ΠΏΡ€Π°Ρ†ΡŽΠ²Π°Ρ‚ΠΈ Π· Ρ€Π΅Π°Π»ΡŒΠ½ΠΈΠΌΠΈ Π΄Π°Π½ΠΈΠΌΠΈ ΠΌΡ–Π»ΡŒΠΉΠΎΠ½Ρ–Π² користувачів, застосовувати NLP-ΠΌΠΎΠ΄Π΅Π»Ρ– Π² ΠΏΡ€ΠΎΠ΄Π°ΠΊΡˆΠ΅Π½Ρ– Ρ‚Π° Ρ€ΠΎΠ·Π²ΠΈΠ²Π°Ρ‚ΠΈ сучасні Recommender Systems β€” приєднуйся.

     

    Π©ΠΎ Π½Π° Ρ‚Π΅Π±Π΅ ΠΎΡ‡Ρ–ΠΊΡƒΡ”:

    • Π ΠΎΠ·Ρ€ΠΎΠ±ΠΊΠ° Ρ‚Π° Ρ€ΠΎΠ·Π²ΠΈΡ‚ΠΎΠΊ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°Ρ†Ρ–ΠΉ для Ρ€Ρ–Π·Π½ΠΎΠ³ΠΎ Ρ‚ΠΈΠΏΡƒ ΠΊΠΎΠ½Ρ‚Π΅Π½Ρ‚Ρƒ;
    • Використання NLP-ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ для покращСння ΠΏΠΎΡˆΡƒΠΊΡƒ Ρ‚Π° пСрсоналізації;
    • Π£Ρ‡Π°ΡΡ‚ΡŒ Ρƒ створСнні ΠΏΡ€ΠΎΠ΄ΡƒΠΊΡ‚Ρ–Π², ΠΏΠΎΠ²'язаних Π· використанням NLP напрямку(Π°Π½Π°Π»Ρ–Π·, ΠΏΠΎΡˆΡƒΠΊ, створСння власних Ρ„Ρ–Ρ‡ Π· тСкстової складової, Ρ‚ΠΎΡ‰ΠΎ);
    • Π ΠΎΠ±ΠΎΡ‚Π° Π· Π²Π΅Π»ΠΈΠΊΠΈΠΌΠΈ масивами ΠΊΠΎΡ€ΠΈΡΡ‚ΡƒΠ²Π°Ρ†ΡŒΠΊΠΈΡ… Π΄Π°Π½ΠΈΡ… для ΠΏΠΎΠ±ΡƒΠ΄ΠΎΠ²ΠΈ ΡƒΠ½Ρ–ΠΊΠ°Π»ΡŒΠ½ΠΈΡ… ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ пСрсоналізації ΠΊΠΎΠ½Ρ‚Π΅Π½Ρ‚Ρƒ;
    • Π£Ρ‡Π°ΡΡ‚ΡŒ Ρƒ ΠΏΠΎΠ±ΡƒΠ΄ΠΎΠ²Ρ– Ρ‚Π° вдосконалСнні ΠΏΠ°ΠΉΠΏΠ»Π°ΠΉΠ½Ρ–Π² для трСнування Ρ‚Π° дСплою ML-ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ;
    • ВСстування Π³Ρ–ΠΏΠΎΡ‚Π΅Π·, запуск A/B СкспСримСнтів Ρ‚Π° інтСрпрСтація Ρ—Ρ… Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ–Π²;
    • Бпівпраця Ρ– ΠΎΠ±ΠΌΡ–Π½ досвідом Π· Ρ–Π½ΡˆΠΈΠΌΠΈ DS-фахівцями для Π²ΠΈΡ€Ρ–ΡˆΠ΅Π½Π½Ρ Π·Π°Π΄Π°Ρ‡ Π² суміТних напрямках.

     

    НСобхідний досвід:

    • 3+ Ρ€ΠΎΠΊΠΈ досвіду Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Π² Ρ€ΠΎΠ»Ρ– Data Scientist Π°Π±ΠΎ ML Engineer;
    • Π’ΠΏΠ΅Π²Π½Π΅Π½Π΅ знання Python Ρ‚Π° Π±Ρ–Π±Π»Ρ–ΠΎΡ‚Π΅ΠΊ для Π°Π½Π°Π»Ρ–Π·Ρƒ Π΄Π°Π½ΠΈΡ… Ρ‚Π° машинного навчання (Pandas, Scikit-learn, PyTorch Π°Π±ΠΎ TensorFlow);
    • Розуміння Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΡ–Π² Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°Ρ†Ρ–ΠΉΠ½ΠΈΡ… систСм: collaborative filtering, matrix factorization, content-based methods, hybrid models, RL;
    • Досвід Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Π· NLP-ΠΏΡ–Π΄Ρ…ΠΎΠ΄Π°ΠΌΠΈ: embedding models, text classification, entity recognition, transformers;
    • Досвід провСдСння складних EDA Π½Π° Ρ€Π΅Π°Π»ΡŒΠ½ΠΈΡ… Π΄Π°Π½ΠΈΡ…;
    • Π‘Π°Π·ΠΎΠ²ΠΈΠΉ досвід Π· MLOps-ΠΏΡ–Π΄Ρ…ΠΎΠ΄Π°ΠΌΠΈ;
    • Розуміння A/B тСстування, ΠΏΠ΅Ρ€Π΅Π²Ρ–Ρ€ΠΊΠΈ статистичних Π³Ρ–ΠΏΠΎΡ‚Π΅Π·;
    • Π”ΠΎΠ±Ρ€Π΅ розуміння SQL Ρ‚Π° Π°Π½Π°Π»Ρ–Π·Π° Π΄Π°Π½ΠΈΡ…: Ρ€ΠΎΠ±ΠΎΡ‚Π° Π· Π±ΡƒΠ΄ΡŒ-якими Π΄ΠΆΠ΅Ρ€Π΅Π»Π°ΠΌΠΈ Π΄Π°Π½ΠΈΡ… (SQL, noSQL, Π²Π΅ΠΊΡ‚ΠΎΡ€Π½Ρ– Π±Π°Π·ΠΈ Π΄Π°Π½ΠΈΡ…, column-oriented Π±Π°Π·ΠΈ Π΄Π°Π½ΠΈΡ… , Ρ‚ΠΎΡ‰ΠΎ).

     

    Π¨ΡƒΠΊΠ°Ρ”ΠΌΠΎ Π»ΡŽΠ΄ΠΈΠ½Ρƒ, яка:

    • ΠœΠ°Ρ” баТання ставати ΡΠΈΠ»ΡŒΠ½Ρ–ΡˆΠ΅ Ρ€Π°Π·ΠΎΠΌ Π· командою;
    • ΠœΠ°Ρ” RnD mindset: розуміння ΠΊΠΎΠ»ΠΈ Ρ‚Ρ€Π΅Π±Π° Π·Ρ€ΠΎΠ±ΠΈΡ‚ΠΈ швидко для ΠΏΠ΅Ρ€Π΅Π²Ρ–Ρ€ΠΊΠΈ Π³Ρ–ΠΏΠΎΡ‚Π΅Π·ΠΈ Ρ– ΠΊΠΎΠ»ΠΈ Π΄ΡƒΠΆΠ΅ якісно, Π±ΠΎ Π²Ρ–Π΄ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρƒ Π·Π°Π»Π΅ΠΆΠΈΡ‚ΡŒ ΠΊΠΎΡ€ΠΈΡΡ‚ΡƒΠ²Π°Ρ†ΡŒΠΊΠΈΠΉ досвід тисяч людСй;
    • Π“ΠΎΡ‚ΠΎΠ²Π° Π²Ρ–Π΄ΠΊΡ€ΠΈΡ‚ΠΎ Π²ΠΈΡΠ»ΠΎΠ²Π»ΡŽΠ²Π°Ρ‚ΠΈ Π±ΡƒΠ΄ΡŒ-які свої Π΄ΡƒΠΌΠΊΠΈ.

     

    Π‘ΡƒΠ΄Π΅ ΠΏΠ΅Ρ€Π΅Π²Π°Π³ΠΎΡŽ:

    • Досвід Π· Elasticsearch Π°Π±ΠΎ Ρ–Π½ΡˆΠΈΠΌΠΈ ΠΏΠΎΡˆΡƒΠΊΠΎΠ²ΠΈΠΌΠΈ систСмами;
    • Досвід Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Π· Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠ°ΠΌΠΈ Π³Π»ΠΈΠ±ΠΎΠΊΠΎΠ³ΠΎ навчання: transformers, reinforcement learning, autoencoders, Ρ‚ΠΎΡ‰ΠΎ.
       

    Π©ΠΎ ΠΌΠΈ ΠΏΡ€ΠΎΠΏΠΎΠ½ΡƒΡ”ΠΌΠΎ:

    • Π ΠΎΠ±ΠΎΡ‚Ρƒ Π² ΡΡ‚Π°Π±Ρ–Π»ΡŒΠ½Ρ–ΠΉ ΠΊΠΎΠΌΠΏΠ°Π½Ρ–Ρ— β€” Π°Π΄ΠΆΠ΅ ΠΌΠΈ ΠΏΠΎΠ½Π°Π΄ 10 Ρ€ΠΎΠΊΡ–Π² Π½Π° Ρ€ΠΈΠ½ΠΊΡƒ;
    • Дійсно Ρ†Ρ–ΠΊΠ°Π²Ρ– завдання: Π±Π΅Ρ€ΠΈ ΡƒΡ‡Π°ΡΡ‚ΡŒ Ρƒ створСнні мСдіасСрвісу ΠΌΠ°ΠΉΠ±ΡƒΡ‚Π½ΡŒΠΎΠ³ΠΎ;
    • Відносини, ΠΏΠΎΠ±ΡƒΠ΄ΠΎΠ²Π°Π½Ρ– Π½Π° Π΄ΠΎΠ²Ρ–Ρ€Ρ–;
    • Π‘Π°Π³Π°Ρ‚ΠΎ моТливостСй для Ρ€ΠΎΠ·Π²ΠΈΡ‚ΠΊΡƒ;
    • НСймовірно ΠΊΡ€ΡƒΡ‚Ρ– ΠΊΠΎΡ€ΠΏΠΎΡ€Π°Ρ‚ΠΈΠ²ΠΈ;
    • Π‘Π΅Π·ΠΊΠΎΡˆΡ‚ΠΎΠ²Π½Ρ– ΡƒΡ€ΠΎΠΊΠΈ Π°Π½Π³Π»Ρ–ΠΉΡΡŒΠΊΠΎΡ— ΠΌΠΎΠ²ΠΈ;
    • Заняття Π· плавання, Π° Ρ‚Π°ΠΊΠΎΠΆ ΡƒΡ€ΠΎΠΊΠΈ Π½Π°ΡΡ‚ΠΎΠ»ΡŒΠ½ΠΎΠ³ΠΎ тСнісу;
    • ΠšΠΎΡ€ΠΏΠΎΡ€Π°Ρ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ психолога;
    • Для співробітників ΠΊΠΎΠΌΠΏΠ°Π½Ρ–Ρ— Π·Π½ΠΈΠΆΠΊΠΈ Π²Ρ–Π΄ Π±Ρ€Π΅Π½Π΄Ρ–Π² ΠΏΠ°Ρ€Ρ‚Π½Π΅Ρ€Ρ–Π².

       

    Ми ΠΏΡ€Π°Π³Π½Π΅ΠΌΠΎ Π±ΡƒΡ‚ΠΈ Ρ€ΠΎΠ±ΠΎΡ‚ΠΎΠ΄Π°Π²Ρ†Π΅ΠΌ, якого ΠΎΠ±ΠΈΡ€Π°ΡŽΡ‚ΡŒ.

    Π‘ΡƒΠ΄Π΅ΠΌΠΎ вдячні, якщо заповниш ΠΊΠΎΡ€ΠΎΡ‚ΠΊΠ΅ опитування ΠΏΡ€ΠΎ Ρ‚Π΅, Ρ‰ΠΎ Π΄Π»Ρ Ρ‚Π΅Π±Π΅ Π²Π°ΠΆΠ»ΠΈΠ²ΠΎ. Π¦Π΅ Π΄ΠΎΠΏΠΎΠΌΠΎΠΆΠ΅ Π½Π°ΠΌ ΠΊΡ€Π°Ρ‰Π΅ Ρ€ΠΎΠ·ΡƒΠΌΡ–Ρ‚ΠΈ очікування ΠΊΠ°Π½Π΄ΠΈΠ΄Π°Ρ‚Ρ–Π² Ρ– ΡΡ‚Π²ΠΎΡ€ΡŽΠ²Π°Ρ‚ΠΈ Ρ‰Π΅ Π±Ρ–Π»ΡŒΡˆ ΠΊΠΎΠΌΡ„ΠΎΡ€Ρ‚Π½Π΅ сСрСдовищС Π² MEGOGO.

     

    Посилання Ρ‚ΡƒΡ‚ - https://bit.ly/43YaxBH

     

    Π’Ρ–Π΄ΠΏΠΎΠ²Ρ–Π΄Π°ΡŽΡ‡ΠΈ Π½Π° Π²Π°ΠΊΠ°Π½ΡΡ–ΡŽ Ρ– Π½Π°Π΄Ρ–ΡΠ»Π°Π²ΡˆΠΈ своє Ρ€Π΅Π·ΡŽΠΌΠ΅ Π² ΠšΠΎΠΌΠΏΠ°Π½Ρ–ΡŽ (Π’ΠžΠ’ Β«ΠœΠ•Π“ΠžΠ“ΠžΒ»), зарСєстровану ΠΉ Π΄Ρ–ΡŽΡ‡Ρƒ Π²Ρ–Π΄ΠΏΠΎΠ²Ρ–Π΄Π½ΠΎ Π΄ΠΎ законодавства Π£ΠΊΡ€Π°Ρ—Π½ΠΈ, рСєстраційний Π½ΠΎΠΌΠ΅Ρ€ 38347009, адрСса: Π£ΠΊΡ€Π°Ρ—Π½Π°, 01011, місто ΠšΠΈΡ—Π², Π²ΡƒΠ».Рибальська, Π±ΡƒΠ΄ΠΈΠ½ΠΎΠΊ 22 (Π΄Π°Π»Ρ– Β«ΠšΠΎΠΌΠΏΠ°Π½Ρ–ΡΒ»), Π²ΠΈ ΠΏΡ–Π΄Ρ‚Π²Π΅Ρ€Π΄ΠΆΡƒΡ”Ρ‚Π΅ Ρ‚Π° погодТуєтСся Π· Ρ‚ΠΈΠΌ, Ρ‰ΠΎ ΠšΠΎΠΌΠΏΠ°Π½Ρ–Ρ обробляє Π²Π°ΡˆΡ– особисті Π΄Π°Π½Ρ–, прСдставлСні Ρƒ Π²Π°ΡˆΠΎΠΌΡƒ Ρ€Π΅Π·ΡŽΠΌΠ΅, Π²Ρ–Π΄ΠΏΠΎΠ²Ρ–Π΄Π½ΠΎ Π΄ΠΎ Π—Π°ΠΊΠΎΠ½Ρƒ Π£ΠΊΡ€Π°Ρ—Π½ΠΈ Β«ΠŸΡ€ΠΎ захист ΠΏΠ΅Ρ€ΡΠΎΠ½Π°Π»ΡŒΠ½ΠΈΡ… Π΄Π°Π½ΠΈΡ…Β» Ρ‚Π° ΠΏΡ€Π°Π²ΠΈΠ» GDPR.

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  • Β· 52 views Β· 3 applications Β· 18d

    Data Scientist

    Office Work Β· Ukraine (Kyiv) Β· Product Β· 3 years of experience
    Π’Ρ–Ρ‚Π°Ρ”ΠΌΠΎ Π² King Group місці, Π΄Π΅ Π·ΡƒΡΡ‚Ρ€Ρ–Ρ‡Π°ΡŽΡ‚ΡŒΡΡ Π½Π°ΠΉΠΊΡ€Π°Ρ‰Ρ– люди Π· IT- Ρ‚Π° Π³Π΅ΠΌΠ±Π»Ρ–Π½Π³-індустрії, Ρ‰ΠΎΠ± Ρ€Π°Π·ΠΎΠΌ Ρ€ΠΎΠ±ΠΈΡ‚ΠΈ Π΄ΠΈΠ²ΠΎΠ²ΠΈΠΆΠ½Ρ– Ρ€Π΅Ρ‡Ρ–. Ми ΠΎΠΏΠ΅Ρ€ΡƒΡ”ΠΌΠΎ числСнними ΠΏΡ€ΠΎΡ”ΠΊΡ‚Π°ΠΌΠΈ Ρƒ сфСрі iGaming Π½Π° Ρ€ΠΈΠ½ΠΊΠ°Ρ… Π£ΠΊΡ€Π°Ρ—Π½ΠΈ, Π„Π²Ρ€ΠΎΠΏΠΈ Ρ‚Π° БША, інвСстуємо Ρƒ Π²Π΅Π½Ρ‡ΡƒΡ€Π½Ρ– стартапи, пСрспСктивні Ρ–Π΄Π΅Ρ—...

    Π’Ρ–Ρ‚Π°Ρ”ΠΌΠΎ Π² King Group γƒΌ місці, Π΄Π΅ Π·ΡƒΡΡ‚Ρ€Ρ–Ρ‡Π°ΡŽΡ‚ΡŒΡΡ Π½Π°ΠΉΠΊΡ€Π°Ρ‰Ρ– люди Π· IT- Ρ‚Π° Π³Π΅ΠΌΠ±Π»Ρ–Π½Π³-індустрії, Ρ‰ΠΎΠ± Ρ€Π°Π·ΠΎΠΌ Ρ€ΠΎΠ±ΠΈΡ‚ΠΈ Π΄ΠΈΠ²ΠΎΠ²ΠΈΠΆΠ½Ρ– Ρ€Π΅Ρ‡Ρ–. Ми ΠΎΠΏΠ΅Ρ€ΡƒΡ”ΠΌΠΎ числСнними ΠΏΡ€ΠΎΡ”ΠΊΡ‚Π°ΠΌΠΈ Ρƒ сфСрі iGaming Π½Π° Ρ€ΠΈΠ½ΠΊΠ°Ρ… Π£ΠΊΡ€Π°Ρ—Π½ΠΈ, Π„Π²Ρ€ΠΎΠΏΠΈ Ρ‚Π° БША, інвСстуємо Ρƒ Π²Π΅Π½Ρ‡ΡƒΡ€Π½Ρ– стартапи, пСрспСктивні Ρ–Π΄Π΅Ρ— Ρ‚Π° людСй. 
    Ми Π°ΠΊΡ‚ΠΈΠ²Π½ΠΎ зростаємо Ρ‚Π° Ρ€ΠΎΠ·ΡˆΠΈΡ€ΡŽΡ”ΠΌΠΎΡΡ, ΡƒΡΠΏΡ–ΡˆΠ½ΠΎ Π·Π°ΠΏΡƒΡΡ‚ΠΈΠ²ΡˆΠΈ Ρ‚Π° Ρ€ΠΎΠ·ΡˆΠΈΡ€ΠΈΠ²ΡˆΠΈ Π½ΠΈΠ·ΠΊΡƒ Π½ΠΎΠ²ΠΈΡ… ΠΏΡ€ΠΎΠ΄ΡƒΠΊΡ‚Ρ–Π² протягом ΠΎΡΡ‚Π°Π½Π½ΡŒΠΎΠ³ΠΎ Ρ€ΠΎΠΊΡƒ.

    Наразі ΠΌΠΈ Ρƒ ΠΏΠΎΡˆΡƒΠΊΠ°Ρ… Data Scientist, Ρ‰ΠΎ Π΄ΠΎΡ”Π΄Π½Π°Ρ”Ρ‚ΡŒΡΡ Ρ‚Π° ΠΏΡ–Π΄ΡΠΈΠ»ΠΈΡ‚ΡŒ Π½Π°ΡˆΡƒ Analytics & Insights ΠΊΠΎΠΌΠ°Π½Π΄Ρƒ.

    ΠžΡΠ½ΠΎΠ²Π½Ρ– Π²ΠΈΠΌΠΎΠ³ΠΈ:
    β€” Π‘Ρ‚ΡƒΠΏΡ–Π½ΡŒ Π±Π°ΠΊΠ°Π»Π°Π²Ρ€Π°/магістра Π°Π±ΠΎ Π΅ΠΊΠ²Ρ–Π²Π°Π»Π΅Π½Ρ‚Π½ΠΈΠΉ досвід Ρƒ Π³Π°Π»ΡƒΠ·Ρ– ΠΌΠ°Ρ‚Π΅ΠΌΠ°Ρ‚ΠΈΠΊΠΈ, статистики, Ρ–Π½Ρ„ΠΎΡ€ΠΌΠ°Ρ‚ΠΈΠΊΠΈ Ρ‡ΠΈ суміТних Π³Π°Π»ΡƒΠ·Π΅ΠΉ;
    β€” Π“Π»ΠΈΠ±ΠΎΠΊΡ– знання ΠΌΠ°Ρ‚Π΅ΠΌΠ°Ρ‚ΠΈΠΊΠΈ, статистики Ρ‚Π° Ρ‚Π΅ΠΎΡ€Ρ–Ρ— ймовірностСй;
    β€” Навички програмування Π½Π° Python;
    β€” Досвід Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Π· Π±Ρ–Π±Π»Ρ–ΠΎΡ‚Π΅ΠΊΠ°ΠΌΠΈ: Pandas, Numpy, Scipy, Scikit-learn, Ρ– Ρ‚Π΄.;
    β€” Досвід Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Ρ–Π· SQL;
    β€” Π“Π»ΠΈΠ±ΠΎΠΊΠ΅ розуміння класичних ML Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΡ–Π²: Clustering, Logistic Regression, Decision Trees, Random Forest, Boostings.

     

    ΠžΠ΄Π½ΠΎΠ·Π½Π°Ρ‡Π½ΠΎ Π±ΡƒΠ΄Π΅ вСликою ΠΏΠ΅Ρ€Π΅Π²Π°Π³ΠΎΡŽ:
    β€” Досвід Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Π· Time Series modeling;
    β€” Досвід Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ DL framework: TensorFlow, PyTorch (+ CUDA);
    β€” Досвід Π· GCP cloud: BigQuery, Cloud Functions.
     
    Π’ΠΎΠ±Ρ– Ρ‚ΠΎΡ‡Π½ΠΎ Π΄ΠΎ нас, якщо Ρ‚ΠΈ:
    β€” Π’ΠΎΠ»ΠΎΠ΄Ρ–Ρ”Ρˆ Π²Ρ–Π΄ΠΌΡ–Π½Π½ΠΈΠΌΠΈ Π°Π½Π°Π»Ρ–Ρ‚ΠΈΡ‡Π½ΠΈΠΌΠΈ Π½Π°Π²ΠΈΡ‡ΠΊΠ°ΠΌΠΈ Ρ‚Π° ΠΊΡ€ΠΈΡ‚ΠΈΡ‡Π½ΠΈΠΌ мислСнням;
    β€” ΠœΠ°Ρ”Ρˆ ΡΠΈΠ»ΡŒΠ½Ρ– ΠΎΡ€Π³Π°Π½Ρ–Π·Π°Ρ‚ΠΎΡ€ΡΡŒΠΊΡ– здібності;
    β€” Π£Π²Π°ΠΆΠ½ΠΈΠΉ Π΄ΠΎ Π΄Π΅Ρ‚Π°Π»Π΅ΠΉ, Π° Ρ‚Π°ΠΊΠΎΠΆ ΠΌΠ°Ρ”Ρˆ Π½Π°Π²ΠΈΡ‡ΠΊΠΈ комплСксного Π²ΠΈΡ€Ρ–ΡˆΠ΅Π½Π½Ρ ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌ, управління часом Ρ– Π»ΠΎΠ³Ρ–ΠΊΠΈ;
    β€” ΠœΠ°Ρ”Ρˆ ΠΆΠ°Π³Ρƒ Π΄ΠΎ Ρ€Ρ–Π·Π½ΠΎΠ³ΠΎ Ρ€ΠΎΠ΄Ρƒ Π΄ΠΎΡΠ»Ρ–Π΄ΠΆΠ΅Π½ΡŒ Ρ‚Π° самовдосконалСння;
    β€” Π’ΠΎΠ»ΠΎΠ΄Ρ–Ρ”Ρˆ Π½Π°Π²ΠΈΡ‡ΠΊΠ°ΠΌΠΈ Π΅Ρ„Π΅ΠΊΡ‚ΠΈΠ²Π½ΠΎΡ— ΠΊΠΎΠΌΡƒΠ½Ρ–ΠΊΠ°Ρ†Ρ–Ρ—, Π·Π΄Π°Ρ‚Π½ΠΈΠΉ Ρ‡Ρ–Ρ‚ΠΊΠΎ Ρ‚Π° Π»Π°ΠΊΠΎΠ½Ρ–Ρ‡Π½ΠΎ прСдставляти Π΄Π°Π½Ρ– ΠΊΠΎΠΌΠ°Π½Π΄Π°ΠΌ Ρ‚Π° Π·Π°Ρ†Ρ–ΠΊΠ°Π²Π»Π΅Π½ΠΈΠΌ сторонам.

    Ми ΠΏΡ€ΠΎΠΏΠΎΠ½ΡƒΡ”ΠΌΠΎ:
    β€” Π’Ρ–Π΄ΡΡƒΡ‚Π½Ρ–ΡΡ‚ΡŒ Π±ΡŽΡ€ΠΎΠΊΡ€Π°Ρ‚Ρ–Ρ— Π² процСсах прийняття Ρ€Ρ–ΡˆΠ΅Π½ΡŒ Ρ– ΠΌΠΎΠΆΠ»ΠΈΠ²Ρ–ΡΡ‚ΡŒ Π±Π΅Π·ΠΏΠΎΡΠ΅Ρ€Π΅Π΄Π½ΡŒΠΎ Π²ΠΏΠ»ΠΈΠ²Π°Ρ‚ΠΈ Π½Π° ΠΏΡ€ΠΎΠ΄ΡƒΠΊΡ‚/ΠΏΡ€ΠΎΡ”ΠΊΡ‚;
    β€” ΠœΠΎΠΆΠ»ΠΈΠ²Ρ–ΡΡ‚ΡŒ навчатися – Π°Π±ΠΎ Π½Π°Π²Ρ‡Π°Ρ‚ΠΈ (ΠΌΠ°Ρ”ΠΌΠΎ ΠΏΡ€ΠΎΡ”ΠΊΡ‚ΠΈ Π· Ρ–Π½Ρ‚Π΅Ρ€Π½Π°Ρ‚ΡƒΡ€ΠΈ Ρ‚Π° мСнторства);
    β€” РСалізація Ρ–Π΄Π΅ΠΉ Ρ‡Π΅Ρ€Π΅Π· власні ΠΏΡ€ΠΎΡ”ΠΊΡ‚ΠΈ;
    β€” НС Π±Ρ–ΠΉΡ‚Π΅ΡΡŒ СкспСримСнтувати! ΠŸΡ€ΠΎΠΏΠΎΠ½ΡƒΠΉΡ‚Π΅ Ρ‚Π° ΠΎΠ²Π½Π΅Ρ€Ρ–Ρ‚ΡŒ процСс Ρ€Π΅Π°Π»Ρ–Π·Π°Ρ†Ρ–Ρ—;
    β€” ΠŸΡ–Π΄Ρ‚Ρ€ΠΈΠΌΡƒΡŽΡ‡Π΅ сСрСдовищС Ρ‚Π° ΠΊΠΎΠΌΠ°Π½Π΄Π°, Ρ–Π· якою ΠΌΠΎΠΆΠ½Π° Ρ€ΠΎΠ±ΠΈΡ‚ΠΈ дійсно ΠΊΡ€ΡƒΡ‚Ρ– ΠΏΡ€ΠΎΠ΄ΡƒΠΊΡ‚ΠΈ, Ρ‰ΠΎ Π·ΠΌΡ–Π½ΡŽΡŽΡ‚ΡŒ Ρ€ΠΈΠ½ΠΎΠΊ;
    β€” Π—Π°Ρ€ΠΏΠ»Π°Ρ‚Ρƒ рівня IT-/iGaming-Ρ€ΠΈΠ½ΠΊΡƒ Ρ‚Π° ΠΏΠΎΠ²Π½ΠΈΠΉ соцпакСт (ΠΌΠ΅Π΄ΠΈΡ‡Π½Π° страховка, ΠΊΠΎΠ½ΡΡƒΠ»ΡŒΡ‚Π°Ρ†Ρ–Ρ— Ρ‚Π΅Ρ€Π°ΠΏΠ΅Π²Ρ‚Π° Π² офісі, компСнсація спортзалу, компСнсація вартості Π»Π°Π½Ρ‡Ρ–Π² Π· Π΄ΠΎΡΡ‚Π°Π²ΠΊΠΎΡŽ Ρ‚ΠΎΡ‰ΠΎ);
    β€” Π—Ρ€ΡƒΡ‡Π½ΠΈΠΉ офіс Ρƒ Ρ†Π΅Π½Ρ‚Ρ€Ρ– ΠšΠΈΡ”Π²Π° (ΠΏΡ–ΡˆΠΊΠΈ Π·Ρ– Π—Π²Ρ–Ρ€ΠΈΠ½Π΅Ρ†ΡŒΠΊΠΎΡ—/Π›ΠΈΠ±Ρ–Π΄ΡΡŒΠΊΠΎΡ—) Ρ–Π· зСлСною ΠΏΠ°Π½ΠΎΡ€Π°ΠΌΠ½ΠΎΡŽ Ρ‚Π΅Ρ€Π°ΡΠΎΡŽ. ΠŸΡ€ΠΎΠ±Π»Π΅ΠΌΠ° Π±Π»Π΅ΠΊΠ°ΡƒΡ‚Ρ–Π² Π²ΠΈΡ€Ρ–ΡˆΠ΅Π½Π° Π½Π° 100%;
    β€” Відпустка - Ρƒ Ρ‚Π΅Π±Π΅ Π±ΡƒΠ΄Π΅ ΠΎΠΏΠ»Π°Ρ‡ΡƒΠ²Π°Π½Π° відпустки Ρ‚Π° Скстравихідні - Π² Скстрадні Π½Π°Π΄Π°Ρ”ΠΌΠΎ Скстравихідні Π½Π°: одруТСння, народТСння Π΄ΠΈΡ‚ΠΈΠ½ΠΈ, Π½Π΅ΠΏΠ΅Ρ€Π΅Π΄Π±Π°Ρ‡ΡƒΠ²Π°Π½Ρ– ΠΏΠΎΠ΄Ρ–Ρ— Ρ‚Π° Ρ–Π½ΡˆΠ΅;
    β€” Бонус Π·Π° Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°Ρ†Ρ–ΡŽ - Ми Π·Π°Π²ΠΆΠ΄ΠΈ Ρ€Π°Π΄Ρ–Ρ”ΠΌΠΎ Ρ‚Π° Ρ†Ρ–Π½ΡƒΡ”ΠΌΠΎ Ρ‚Π΅, Ρ‰ΠΎ Ρ‚Ρ–ΠΌΠΌΠ΅ΠΉΡ‚ΠΈ Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄ΡƒΡŽΡ‚ΡŒ своїх Π΄Ρ€ΡƒΠ·Ρ–Π², Ρ‚ΠΎΠΌΡƒ Π΄ΠΎ ΠΏΠ»ΡŽΡΡ–Π² Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Π· ΠΏΠ΅Ρ€Π΅Π²Ρ–Ρ€Π΅Π½ΠΎΡŽ Ρ‚Π° Π½Π°Π΄Ρ–ΠΉΠ½ΠΎΡŽ людиною ΠΌΠΈ Π΄ΠΎΠ΄Π°Ρ”ΠΌΠΎ бонус;
    β€” Π Π΅Π»ΠΎΠΊΠ΅ΠΉΡ‚ - Π·ΠΌΡ–Π½Π° міста проТивання Π·Π°Π²ΠΆΠ΄ΠΈ спонукає Π΄ΠΎ Π΄ΠΎΠ΄Π°Ρ‚ΠΊΠΎΠ²ΠΈΡ… Π²ΠΈΡ‚Ρ€Π°Ρ‚, Π° наш бонус Π΄ΠΎΠΏΠΎΠΌΠ°Π³Π°Ρ” ΠΏΡ€ΠΎΠΉΡ‚ΠΈ Ρ†Π΅ΠΉ ΠΏΠ΅Ρ€Ρ–ΠΎΠ΄ Π±Π΅Π· Π·Π°ΠΉΠ²ΠΈΡ… стрСсів.

    Π―ΠΊΡ‰ΠΎ Ρ‚ΠΈ ΡˆΡƒΠΊΠ°Ρ”Ρˆ для сСбС ΡΡ‚Π°Π±Ρ–Π»ΡŒΠ½Ρƒ ΠΊΠΎΠΌΠΏΠ°Π½Ρ–ΡŽ Π· класними людьми Ρ‚Π° ΠΌΠΎΠΆΠ»ΠΈΠ²Ρ–ΡΡ‚ΡŽ росту - Ρ‚ΠΎΠ±Ρ– Π΄ΠΎ нас! Відправляй Ρ€Π΅Π·ΡŽΠΌΠ΅!

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  • Β· 12 views Β· 0 applications Β· 1d

    Game Mathematician to $3000

    Hybrid Remote Β· Poland Β· Product Β· 3 years of experience Β· Intermediate
    Π£ NeverEnding ΠΌΠΈ ΡΡ‚Π²ΠΎΡ€ΡŽΡ”ΠΌΠΎ Ρ–Π³Ρ€ΠΈ, які дійсно β€œΠ·Π°Ρ‚ΡΠ³ΡƒΡŽΡ‚ΡŒβ€ β€” Ρ– Π·Π°Ρ€Π°Π· ΡˆΡƒΠΊΠ°Ρ”ΠΌΠΎ Game Mathematician’a, який Π΄ΠΎΠΏΠΎΠΌΠΎΠΆΠ΅ Π½Π°ΠΌ Ρ€ΠΎΠ·Ρ€ΠΎΠ±ΠΈΡ‚ΠΈ ΠΌΠ΅Ρ…Π°Π½Ρ–ΠΊΠΈ, Ρ‰ΠΎ ΠΏΡ€ΠΈΠ½ΠΎΡΡΡ‚ΡŒ задоволСння Π³Ρ€Π°Π²Ρ†ΡŽ ΠΉ Π΄ΠΎΡ…Ρ–Π΄ бізнСсу. Π¦Π΅ Ρ€ΠΎΠ»ΡŒ для Ρ‚ΠΈΡ…, Ρ…Ρ‚ΠΎ Ρ…ΠΎΡ‡Π΅ Π±ΡƒΠ΄ΡƒΠ²Π°Ρ‚ΠΈ Π½ΠΎΠ²Ρ– Ρ–Π³Ρ€ΠΈ Π· нуля, ΠΏΡ€Π°Ρ†ΡŽΠ²Π°Ρ‚ΠΈ Π·...

    Π£ NeverEnding ΠΌΠΈ ΡΡ‚Π²ΠΎΡ€ΡŽΡ”ΠΌΠΎ Ρ–Π³Ρ€ΠΈ, які дійсно β€œΠ·Π°Ρ‚ΡΠ³ΡƒΡŽΡ‚ΡŒβ€ β€” Ρ– Π·Π°Ρ€Π°Π· ΡˆΡƒΠΊΠ°Ρ”ΠΌΠΎ Game Mathematician’a, який Π΄ΠΎΠΏΠΎΠΌΠΎΠΆΠ΅ Π½Π°ΠΌ Ρ€ΠΎΠ·Ρ€ΠΎΠ±ΠΈΡ‚ΠΈ ΠΌΠ΅Ρ…Π°Π½Ρ–ΠΊΠΈ, Ρ‰ΠΎ ΠΏΡ€ΠΈΠ½ΠΎΡΡΡ‚ΡŒ задоволСння Π³Ρ€Π°Π²Ρ†ΡŽ ΠΉ Π΄ΠΎΡ…Ρ–Π΄ бізнСсу.

     

    Π¦Π΅ Ρ€ΠΎΠ»ΡŒ для Ρ‚ΠΈΡ…, Ρ…Ρ‚ΠΎ Ρ…ΠΎΡ‡Π΅ Π±ΡƒΠ΄ΡƒΠ²Π°Ρ‚ΠΈ Π½ΠΎΠ²Ρ– Ρ–Π³Ρ€ΠΈ Π· нуля, ΠΏΡ€Π°Ρ†ΡŽΠ²Π°Ρ‚ΠΈ Π· Ρ€Ρ–Π·Π½ΠΈΠΌΠΈ ΠΆΠ°Π½Ρ€Π°ΠΌΠΈ (слоти, інстант, crash) Ρ‚Π° Π²ΠΏΠ»ΠΈΠ²Π°Ρ‚ΠΈ Π½Π° ΠΊΠΎΠΆΠ½Ρƒ Ρ†ΠΈΡ„Ρ€Ρƒ, яка Π·β€™ΡΠ²Π»ΡΡ”Ρ‚ΡŒΡΡ Ρƒ Π³Ρ€Ρ–.

     

    Π©ΠΎ Ρ€ΠΎΠ±ΠΈΡ‚ΠΈ:

    • ΠŸΡ€ΠΎΡ”ΠΊΡ‚ΡƒΠ²Π°Ρ‚ΠΈ Ρ–Π³Ρ€ΠΎΠ²Ρƒ ΠΌΠ°Ρ‚Π΅ΠΌΠ°Ρ‚ΠΈΠΊΡƒ: RTP, volatilities, hit frequency, distribution curves.
    • Розробляти ΠΌΠ°Ρ‚Π΅ΠΌΠ°Ρ‚ΠΈΡ‡Π½Ρ– ΠΌΠΎΠ΄Π΅Π»Ρ– для слотів, instant- Ρ‚Π° crash-Ρ–Π³ΠΎΡ€.
    • ΠŸΠΈΡΠ°Ρ‚ΠΈ симуляції Ρ‚Π° Π°Π½Π°Π»Ρ–Π·ΡƒΠ²Π°Ρ‚ΠΈ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΈ для балансування.
    • ΠŸΡ€Π°Ρ†ΡŽΠ²Π°Ρ‚ΠΈ Ρ€Π°Π·ΠΎΠΌ Ρ–Π· Π³Π΅ΠΉΠΌ-Π΄ΠΈΠ·Π°ΠΉΠ½Π΅Ρ€Π°ΠΌΠΈ, Ρ…ΡƒΠ΄ΠΎΠΆΠ½ΠΈΠΊΠ°ΠΌΠΈ, ΠΏΡ€ΠΎΠ΄Π°ΠΊΡ‚Π°ΠΌΠΈ Ρ‚Π° Π΄Π΅Π²Π°ΠΌΠΈ для створСння цілісного Ρ–Π³Ρ€ΠΎΠ²ΠΎΠ³ΠΎ досвіду.
    • Π’ΠΈΠ·Π½Π°Ρ‡Π°Ρ‚ΠΈ Ρ‚Π΅Ρ…Π½Ρ–Ρ‡Π½Ρ– обмСТСння, Ρ€ΠΈΠ·ΠΈΠΊΠΈ, Ρ‚Π° Π·Π½Π°Ρ…ΠΎΠ΄ΠΈΡ‚ΠΈ Ρ€Ρ–ΡˆΠ΅Π½Π½Ρ Π½Π° Π΅Ρ‚Π°ΠΏΡ– ΠΊΠΎΠ½Ρ†Π΅ΠΏΡ‚Ρƒ.

     

    Кого ΠΌΠΈ ΡˆΡƒΠΊΠ°Ρ”ΠΌΠΎ:

    • 3+ Ρ€ΠΎΠΊΠΈ досвіду Π² Ρ–Π³Ρ€ΠΎΠ²Ρ–ΠΉ ΠΌΠ°Ρ‚Π΅ΠΌΠ°Ρ‚ΠΈΡ†Ρ– Π°Π±ΠΎ Π³Π΅ΠΉΠΌ-Π΄ΠΈΠ·Π°ΠΉΠ½Ρ– Π· ΠΌΠ°Ρ‚Π΅ΠΌΠ°Ρ‚ΠΈΡ‡Π½ΠΈΠΌ ΡƒΡ…ΠΈΠ»ΠΎΠΌ.
    • Π“Π»ΠΈΠ±ΠΎΠΊΠ΅ розуміння слот-ΠΌΠ΅Ρ…Π°Π½Ρ–ΠΊ, RTP, volatilities, bonus systems.
    • Π’ΠΏΠ΅Π²Π½Π΅Π½Π΅ володіння Excel / Google Sheets, Python Π°Π±ΠΎ Ρ–Π½ΡˆΠΈΠΌ інструмСнтом для симуляцій.
    • Досвід Ρ–Π· балансуванням Payout Tables Ρ– Free Spins - Π²Π΅Π»ΠΈΠΊΠΈΠΉ плюс.
    • АналітичнС мислСння, ΡƒΠ²Π°ΠΆΠ½Ρ–ΡΡ‚ΡŒ Π΄ΠΎ Π΄Π΅Ρ‚Π°Π»Π΅ΠΉ, Π·Π΄Π°Ρ‚Π½Ρ–ΡΡ‚ΡŒ ΠΎΠΏΡ‚ΠΈΠΌΡ–Π·ΡƒΠ²Π°Ρ‚ΠΈ складнС.

     

    Ми ΡˆΡƒΠΊΠ°Ρ”ΠΌΠΎ Π»ΡŽΠ΄ΠΈΠ½Ρƒ, яка:

    • Π”ΡƒΠΌΠ°Ρ” як Π³Ρ€Π°Π²Π΅Ρ†ΡŒ Ρ– ΠΌΠΈΡΠ»ΠΈΡ‚ΡŒ як Π°Π½Π°Π»Ρ–Ρ‚ΠΈΠΊ.
    • Π£ΠΌΡ–Ρ” Π±ΡƒΠ΄ΡƒΠ²Π°Ρ‚ΠΈ ΠΌΠΎΠ΄Π΅Π»Ρ–, Ρ‰ΠΎ Π²Ρ–Π΄ΠΏΠΎΠ²Ρ–Π΄Π°ΡŽΡ‚ΡŒ як Π³Π΅ΠΉΠΌΠΏΠ»Π΅ΠΉΠ½ΠΈΠΌ, Ρ‚Π°ΠΊ Ρ– бізнСс-цілям.
    • Π₯ΠΎΡ‡Π΅ ΠΏΡ€Π°Ρ†ΡŽΠ²Π°Ρ‚ΠΈ Π· Π½ΠΎΠ²ΠΈΠΌΠΈ ідСями, Π° Π½Π΅ ΡˆΡ‚Π°ΠΌΠΏΡƒΠ²Π°Ρ‚ΠΈ Ρ‚ΠΈΠΏΠΎΠ²Ρ– Ρ„Ρ–Ρ‡Ρ–.
    • Π›ΡŽΠ±ΠΈΡ‚ΡŒ Ρ†ΠΈΡ„Ρ€ΠΈ, СкспСримСнти Ρ– Ρ‡Π΅Π»Π΅Π½Π΄ΠΆΡ–.

     

    Π§ΠΎΠΌΡƒ Π²Π°Ρ€Ρ‚ΠΎ приєднатися Π΄ΠΎ NeverEnding?

    • Π ΠΎΠ±ΠΎΡ‚Π° Π· нуля Π½Π°Π΄ ΠΏΠ΅Ρ€ΡˆΠΈΠΌΠΈ Ρ–Π³Ρ€Π°ΠΌΠΈ ΠΊΠΎΠΌΠΏΠ°Π½Ρ–Ρ—.
    • Π’ΠΏΠ»ΠΈΠ² Π½Π° формування Ρ–Π³Ρ€ΠΎΠ²ΠΎΡ— Π»Ρ–Π½Ρ–ΠΉΠΊΠΈ ΠΉ math-напряму Π² ΠΊΠΎΠΌΠ°Π½Π΄Ρ–.
    • ΠŸΡ€ΡΠΌΠ° співпраця Π· Ρ„Π°ΡƒΠ½Π΄Π΅Ρ€Π°ΠΌΠΈ Ρ‚Π° ΠΏΡ€ΠΎΠ΄ΡƒΠΊΡ‚ΠΎΠ²ΠΎΡŽ командою.
    • Π“Π½ΡƒΡ‡ΠΊΡ–ΡΡ‚ΡŒ, ΡˆΠ²ΠΈΠ΄ΠΊΡ–ΡΡ‚ΡŒ Ρ– Π²Ρ–Π΄ΠΊΡ€ΠΈΡ‚Π΅ ΠΏΠΎΠ»Π΅ для творчості.
    • Π‘Ρ‚Π°Ρ€Ρ‚Π°ΠΏ Ρ–Π· Π°ΠΌΠ±Ρ–Ρ†Ρ–Ρ”ΡŽ стати ΠΏΡ€ΠΎΠ²Π°ΠΉΠ΄Π΅Ρ€ΠΎΠΌ Π½ΠΎΠ²ΠΎΠ³ΠΎ покоління.

     

    πŸ“ Π€ΠΎΡ€ΠΌΠ°Ρ‚: Remote / Hybrid β€” Π½Π° Ρ‚Π²Ρ–ΠΉ Π²ΠΈΠ±Ρ–Ρ€

    πŸ• Π€ΠΎΡ€ΠΌΠ°Ρ‚: Повна Π·Π°ΠΉΠ½ΡΡ‚Ρ–ΡΡ‚ΡŒ | 40 Π³ΠΎΠ΄/Ρ‚ΠΈΠΆΠ΄Π΅Π½ΡŒ | 5/2

    πŸ’° Π—Π°Ρ€ΠΏΠ»Π°Ρ‚Π°: ΠšΠΎΠ½ΠΊΡƒΡ€Π΅Π½Ρ‚Π½Π° β€” ΠΎΠ±Π³ΠΎΠ²ΠΎΡ€ΡŽΡ”Ρ‚ΡŒΡΡ

     

    Π―ΠΊΡ‰ΠΎ Ρ‚ΠΈ Ρ…ΠΎΡ‡Π΅Ρˆ ΡΡ‚Π²ΠΎΡ€ΡŽΠ²Π°Ρ‚ΠΈ Π½ΠΎΠ²Ρ– світи Ρ‡Π΅Ρ€Π΅Π· Ρ„ΠΎΡ€ΠΌΡƒΠ»ΠΈ Ρ‚Π° Ρ†ΠΈΡ„Ρ€ΠΈ β€” приєднуйся.

    NeverEnding Ρ‚Ρ–Π»ΡŒΠΊΠΈ ΠΏΠΎΡ‡ΠΈΠ½Π°Ρ”Ρ‚ΡŒΡΡ.

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