Jobs
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Β· 94 views Β· 17 applications Β· 27d
Computer Vision Engineer
Ukraine Β· Product Β· 3 years of experience Β· Intermediate MilTech πͺEmployeer - defense tech company specializing in the development of innovative solutions in the direction of Embedded systems and radio frequency (RF) engineering. Responsibilities: β’β β Develop and implement computer vision algorithms using both...Employeer - defense tech company specializing in the development of innovative solutions in the direction of Embedded systems and radio frequency (RF) engineering.
Responsibilities:
β’β β Develop and implement computer vision algorithms using both classical techniques and neural networks.
β’β β Utilize and understand popular networks and their building blocks in computer vision tasks.Requirements:
β’β β Proven experience with classical computer vision and neural networks
β’β β Strong understanding of geometrical computer vision principles
β’β β Hands-on experience in implementing low-level CV algorithms
β’β β In-depth knowledge of popular computer vision networks and components
β’β β Ability to quickly navigate through recent research and trends in computer vision
β’β β Proficiency in Python or C++
β’β β Proficiency in SLAM/VIO
β’β β Experience with Linux
β’β β Extensive experience with common frameworks/libraries used for computer vision (OpenCV, numpy, PyTorch, ONNX, Eigen, etc.)Working conditions:
- Full employment
- Work from the office in Kyiv or full remote
- Official employment
- Reservation from mobilization
- 24 calendar days of vacation and paid sick leave
- A dynamic, innovative and large-scale team working on a number of new products and improving current products
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Lobby X is a socially responsible business, a unique combination of the job platform and full-cycle recruiting agency, specializing in hiring top talents for government, business, tech, miltech, and progressive non-governmental organizations in Ukraine and globally. -
Β· 87 views Β· 8 applications Β· 19d
Data Scientist / Quantitative Researcher
Full Remote Β· Worldwide Β· Product Β· 3 years of experienceWe 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 weβre 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.
π Now weβre 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:
β solving algorithmic trading problems: regression/autoregression, classification of timeseries/financial series, working with cryptocurrency quotes.
Whatβs in it for you?π₯ Health first: Comprehensive medical insurance.
π€ Keep growing: We cover courses, conferences, training sessions, and workshops.
πͺ Stay active mentally and physically : Sports / hobby / personal psychologist to fuel yourself.
πΌ We've got your back: Access to legal assistance when you need it.
π§ββοΈ Inspiring vibes: Join a motivated, goal-oriented team that supports each other.
π§βπ» Make a difference: Have a direct impact on shaping and growing the product.
π» Work smarter: Corporate laptops to help you do your best work.
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Join our team and help us level up! -
Β· 28 views Β· 1 application Β· 10d
Data Scientist / ML Engineer (AWS) for Fitness Studio Business
Full Remote Β· Poland Β· Product Β· 3 years of experience Β· Upper-IntermediateProject Description: We are looking for a Data Scientist / Machine Learning Engineer to develop and implement an ML solution that predicts key business metrics for fitness studios (sales, visits, contract signings, customer indicators) based on...Project Description:
We are looking for a Data Scientist / Machine Learning Engineer to develop and implement an ML solution that predicts key business metrics for fitness studios (sales, visits, contract signings, customer indicators) based on historical data. The project will be deployed on AWS.
iKizmet (www.ikizmet.com) is a fast-growing analytics software company specializing in the health and fitness industry. We are integrated with the largest POS and Scheduling platforms in our industry and our client list has some of the largest brands in the boutique fitness space.
Job Title: Data Scientist / ML Engineer (AWS) for Fitness Studio Business Forecasting Project
Responsibilities:
β’ Analyze data from fitness studios: sales, visits, contracts, and customer data.
β’ Build end-to-end ML pipelines (data preprocessing β model training β testing β deployment β monitoring).
β’ Develop forecasting models (regression, classification, time series).
β’ Implement data pipelines and ML workflows on AWS (SageMaker, S3, Glue, Lambda).
β’ Set up model performance monitoring and reporting.
β’ Prepare reports and visualize results for business stakeholders.
β’ Collaborate with team members and stakeholders to align tasks and communicate results.
Requirements:
β’ 3+ years of experience as a Data Scientist / ML Engineer.
β’ Strong Python skills (pandas, numpy, scikit-learn, PyTorch or equivalent).
β’ Experience with ETL pipelines and working with large datasets.
β’ Hands-on experience with time series, regression, and classification models.
β’ Proven experience with AWS: SageMaker, S3, Glue, Lambda, CloudWatch.
β’ Proficiency in SQL.
β’ Ability to clearly explain technical solutions to business stakeholders.
β’ English proficiency (Intermediate or higher) for working in an international environment. Nice to have:
β’ Experience building BI dashboards (e.g., AWS QuickSight, Power BI, Tableau).
β’ MLOps and CI/CD experience.
We offer:
β’ Work on a real-world ML project with impactful business data. β’ Collaboration with an international team.
β’ Flexible schedule, fully remote work.
β’ Opportunities for learning, professional growth, and career development.
Working hours: 11 AM - 7 PM CET
Please let me know if you are interested in our offer.
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Β· 44 views Β· 6 applications Β· 11d
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-IntermediateWe are elai.io, an innovative AI-driven startup specializing in video generation. Recently acquired by Panopto β a leader in interactive video solutions β weβre 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 weβre now part of a growing team of around 200 professionals focused on advancing learning through powerful, interactive video technology.
What Youβll 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 Masterβs 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:
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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 -
Β· 22 views Β· 3 applications Β· 20d
Game Mathematician
Full Remote Β· EU Β· Product Β· 3 years of experience Β· Upper-IntermediateWe 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 Companyβs 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 designersβ games and concepts;
- Contributing to the evolution of the teamβs 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· 33 views Β· 0 applications Β· 6d
Data Scientist (NLP + LLMs)
Full Remote Β· Ukraine Β· 3 years of experienceWe 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 (Bachelorβs 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· 73 views Β· 18 applications Β· 30d
Principal/Senior Marketing Analyst to $6000
Full Remote Β· Worldwide Β· Product Β· 3 years of experience Β· Upper-IntermediateAtom Apps β a fast-growing, AI-powered mobile app company with 15M+ U.S. downloads. They specialize in end-to-end mobile app development, monetization, and distribution across various verticals. Now, Atom Apps is hiring a Marketing Analyst. Key...Atom Apps β a fast-growing, AI-powered mobile app company with 15M+ U.S. downloads. They specialize in end-to-end mobile app development, monetization, and distribution across various verticals.
Now, Atom Apps is hiring a Marketing Analyst.
Key responsibilities:
- Evaluate paid campaign effectiveness and work closely with marketers to achieve better profitability.
- Work closely with the marketing team to align on goals and optimize lead-to-revenue performance.
- Use data to identify high-value segments, guide personalization strategies, and improve conversion rates across the funnel.
- Perform cohort analyses, funnel evaluations, and churn investigations to uncover growth opportunities and user friction points on different acquisition channels.
- Build scalable SQL queries, data models, and BI dashboards (e.g., in Tableau, Looker, Power BI) to support self-serve analytics and empower team autonomy.
- Build and update LTV prediction models.
- Collaborate with data engineering to ensure clean, scalable, and real-time data pipelines.
- Be a thought partner to CMO, Head of Product, and CEO, while driving company bets, not just reporting metrics.
- Try out different mathematical modeling methods to attribute organic traffic by channel.
Must-have technology & skill requirements:
- Advanced SQL: ability to write complex queries for large, distributed datasets.
- Proficiency in data visualization tools such as Tableau, Looker, Power BI, or similar.
- Strong skills in Python or R for statistical analysis, modeling, and automation.
- Familiarity with data warehousing and analytics engineering tools, and creating ETL Models (e.g., dbt).
Nice-to-have technology & skill requirements:
- Experience in marketing analytics, business intelligence, or data analysis, ideally in tech.
- Hands-on experience with multichannel campaign analysis (especially paid search, paid social, email, and web).
Why Join Atom Apps?
- π Fully Remote β Work from anywhere in the world
- π° Competitive Pay & Benefits
- π± Growth Opportunities β International exposure & cross-functional collaboration
- βοΈ Modern Tech Stack β Access to the latest AI models and marketing tools
- π€ Global Team β Work with top-tier talent across continents
π§ Real Ownership β Make a visible impact on our product and business
Join Us in Building the Future of AI-Powered Consumer Apps
If youβre passionate about scaling mobile apps through performance marketing and want to work with a dynamic, international team, we want to hear from you!
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Β· 46 views Β· 5 applications Β· 26d
Fractional Mathematician
Part-time Β· Full Remote Β· Worldwide Β· 3 years of experience Β· Upper-IntermediateSwipe Games is seeking a Fractional Mathematician with deep iGaming expertise to design, analyze, and optimize game mechanics and payout structures. This is a hands-on, high-impact consulting role for an expert who understands both the creative and...Swipe Games is seeking a Fractional Mathematician with deep iGaming expertise to design, analyze, and optimize game mechanics and payout structures. This is a hands-on, high-impact consulting role for an expert who understands both the creative and regulatory demands of modern game math. You will collaborate closely with our core team to ensure our products deliver engaging, fair, and profitable experiences for players and partners.
Key Requirements
- Proven experience designing and analyzing game math for successful, high-load iGaming products
- Deep understanding of probability theory, statistics, and stochastic modeling as applied to games of chance and skill
- Familiarity with regulatory and compliance requirements for game mathematics in key iGaming markets
- Experience with provably fair algorithms and cryptography in gaming contexts, RNG certification
- Strong business orientation: ability to balance player engagement, fairness, and monetization
- High level of ownership and initiative in delivering mathematical solutions
Responsibilities
- Design and validate mathematical models and payout structures for new and existing games
- Collaborate with product, engineering, and compliance teams to ensure math models meet regulatory and business requirements
- Analyze game performance, volatility, and player behavior to optimize engagement and profitability
- Develop and review provably fair algorithms and cryptographic solutions for game outcomes
- Provide ad-hoc mathematical support for partner integrations, risk management, and game audits
- Document and present mathematical concepts and models to both technical and non-technical stakeholders
What We Offer
- Opportunity to shape the core mechanics of breakthrough iGaming products
- Flexible, high-ownership engagement with a next-gen product team
- Collaboration with industry experts in a dynamic, innovation-driven environment
- Competitive compensation for fractional consulting
If you are a mathematician with a passion for iGaming innovation and a proven record of delivering robust, compliant game math, we want to hear from you.
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Β· 46 views Β· 4 applications Β· 25d
Senior Game Mathematician
Full Remote Β· Countries of Europe or Ukraine Β· Product Β· 3 years of experience Β· IntermediateFAVBET Tech develops software that is used by millions of players around the world for the international company FAVBET Entertainment. We develop innovations in the field of gambling and betting through a complex multi-component platform which is capable...FAVBET Tech develops software that is used by millions of players around the world for the international company FAVBET Entertainment.
We develop innovations in the field of gambling and betting through a complex multi-component platform which is capable to withstand enormous loads and provide a unique experience for players.
FAVBET Tech does not organize and conduct gambling on its platform. Its main focus is software development.
Main areas of work:- Betting/Gambling Platform Software Development β software development that is easy to use and personalized for each customer.
- Highload Development β development of highly loaded services and systems.
- CRM System Development β development of a number of services to ensure a high level of customer service, effective engagement of new customers and retention of existing ones.
- Big Data β development of complex systems for processing and analysis of big data.
- Cloud Services β we use cloud technologies for scaling and business efficiency.
Responsibilities:
- Developing and design the math side of casino games, mostly slot machines
- Determine and calculate the probabilities, build game behavior and properties
- Cooperate with product managers and developers
- Come up with new and innovative ideas and also be aware of existing features in the industry
- Maintenance of existing games
- Work closely with development teams
Requirements:
- BS/MS degree in Mathematics, statistics or similar disciplines with a very strong mathematical skill
- Experience in gaming industry 2+ years
- Extremely details oriented, fast learning and highly motivated person
- Creative, productive, working as part of a team, responsible
- Basic programming knowledge
- Advanced programming β advantage
- Strong communication skills
We offer:
- 30 day off β we value rest and recreation;
- Medical insurance for employees and the possibility of training employees at the expense of the company and gym membership;
- Remote work or the opportunity β our own modern lofty office with spacious workplace, and brand-new work equipment (near Pochaina metro station);
- Flexible work schedule β we expect a full-time commitment but do not track your working hours;
- Flat hierarchy without micromanagement β our doors are open, and all teammates are approachable.
During the war, the company actively supports the Ministry of Digital Transformation of Ukraine in the initiative to deploy an IT army and has already organized its own cyber warfare unit, which makes a crushing blow to the enemyβs IT infrastructure 24/7, coordinates with other cyber volunteers and plans offensive actions on its IT front line.
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Β· 39 views Β· 4 applications Β· 23d
AI Data Architect β Agentic AI Platform for BFSI
Full Remote Β· Countries of Europe or Ukraine Β· 3 years of experience Β· Upper-IntermediateWe're seeking a talented Data Architect to join our innovative startup, developing Guppy (GenAI Unified Platform for Performance and Yield)βa 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)βa 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.
π― Your Mission at Guppy
You'll play a pivotal role in designing and implementing data infrastructure tailored for BFSI software engineering needs. Youβll 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.
π 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.
π 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.
ποΈ 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· 29 views Β· 1 application Β· 18d
Senior Machine Learning Ops Engineer
Full Remote Β· Ukraine, Poland Β· 3.5 years of experience Β· Upper-IntermediateDescription 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 clientβs culture is based on mutual trust, sharing, building, and learning together. They value simplicity, maintainability, automation, and metrics.About this role:
Clientβs 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.
Clientβs 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. Youβll play a leading role in significantly scaling this further.
As clientβs 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. Youβll 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. Youβll 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 environmentsJob responsibilities
Model Deployment and Operations:
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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 -
Β· 52 views Β· 12 applications Β· 10d
Senior Parsing and Data Extraction Engineer
Full Remote Β· Worldwide Β· 3 years of experienceAltss 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 βhiddenβ 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 infrastructureβhandling 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· 57 views Β· 1 application Β· 5d
Machine Learning Engineer
Full Remote Β· Countries of Europe or Ukraine Β· 3 years of experience Β· Upper-IntermediateAIMPROSOFT 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 companyβs projects. About the role: ...
πAIMPROSOFT 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 companyβs projects.π―About the role:
In this role, you will be responsible for contribute to the companyβs 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.
π₯What We Need From You:- 3+ years as a Machine Learning Engineer, Data Scientist or AI Engineer
- Πxperience 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.
πΌWhat 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· 52 views Β· 7 applications Β· 30d
Data Scientist
Full Remote Β· Ukraine Β· 3 years of experience Β· IntermediateΠ‘ΡΠ°Π½ΡΡΠ΅ ΡΠ°ΡΡΠΈΠ½ΠΎΡ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ, ΡΠΎ ΡΡΠ²ΠΎΡΡΡ ΡΠΈΡΡΠΎΠ²Ρ ΡΠ΅Π°Π»ΡΠ½ΡΡΡΡ! MODUS X β ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠ° ΠΠ’-ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ, ΠΊΠΎΠΌΠ°Π½Π΄Π° 650+ ΡΠ½ΠΆΠ΅Π½Π΅ΡΡΠ², Π°ΡΡ ΡΡΠ΅ΠΊΡΠΎΡΡΠ², ΡΠΏΠ΅ΡΡΠ°Π»ΡΡΡΡΠ² Π· Π±Π΅Π·ΠΏΠ΅ΠΊΠΈ ΡΠ° Π΄Π°ΡΠ°ΡΠ°ΡΠ½ΡΠΈΡΡΡΠ².β ΠΠΈ ΡΠΎΠ·ΠΏΠΎΡΠ°Π»ΠΈ ΡΠ° ΠΏΡΠΎΠ΄ΠΎΠ²ΠΆΡΡΠΌΠΎ ΡΡΠΏΡΠΎΠ²ΡΠ΄ ΡΠΈΡΡΠΎΠ²ΠΎΡ ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΡΡ ΠΠ’ΠΠ, ΡΠΊΠ° ΠΏΠ΅ΡΡΠΎΡ Π²...Π‘ΡΠ°Π½ΡΡΠ΅ ΡΠ°ΡΡΠΈΠ½ΠΎΡ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ, ΡΠΎ ΡΡΠ²ΠΎΡΡΡ ΡΠΈΡΡΠΎΠ²Ρ ΡΠ΅Π°Π»ΡΠ½ΡΡΡΡ!
MODUS X β ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠ° ΠΠ’-ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ, ΠΊΠΎΠΌΠ°Π½Π΄Π° 650+ ΡΠ½ΠΆΠ΅Π½Π΅ΡΡΠ², Π°ΡΡ ΡΡΠ΅ΠΊΡΠΎΡΡΠ², ΡΠΏΠ΅ΡΡΠ°Π»ΡΡΡΡΠ² Π· Π±Π΅Π·ΠΏΠ΅ΠΊΠΈ ΡΠ° Π΄Π°ΡΠ°ΡΠ°ΡΠ½ΡΠΈΡΡΡΠ².β ΠΠΈ ΡΠΎΠ·ΠΏΠΎΡΠ°Π»ΠΈ ΡΠ° ΠΏΡΠΎΠ΄ΠΎΠ²ΠΆΡΡΠΌΠΎ ΡΡΠΏΡΠΎΠ²ΡΠ΄ ΡΠΈΡΡΠΎΠ²ΠΎΡ ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΡΡ ΠΠ’ΠΠ, ΡΠΊΠ° ΠΏΠ΅ΡΡΠΎΡ Π² Π΅Π½Π΅ΡΠ³Π΅ΡΠΈΡΡ Π£ΠΊΡΠ°ΡΠ½ΠΈ ΡΡΠ°Π»Π° Π½Π° ΡΠ»ΡΡ ΠΌΠ°ΡΡΡΠ°Π±Π½ΠΎΠ³ΠΎ Π΄ΡΠ΄ΠΆΠΈΡΠ°Π»-ΠΏΠ΅ΡΠ΅ΡΠ²ΠΎΡΠ΅Π½Π½Ρ. ΠΠΈΠ½Ρ Π²ΠΈΠ΄ΡΠ»ΠΈΠ»ΠΈΡΡ Π² ΠΎΠΊΡΠ΅ΠΌΡ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ, ΡΠΎΠ±ΠΈ Π΄ΡΠ»ΠΈΡΠΈΡΡ ΡΠ²ΠΎΡΠΌ Π΄ΠΎΡΠ²ΡΠ΄ΠΎΠΌ ΡΠ° Π΅ΠΊΡΠΏΠ΅ΡΡΠΈΠ·ΠΎΡ Π½Π°Π·ΠΎΠ²Π½Ρ, Π·Π°Π»ΠΈΡΠ°ΡΡΠΈΡΡ ΠΠ’-ΠΎΠΏΠΎΡΠΎΡ Π΄Π»Ρ ΡΠΈΡ , Ρ ΡΠΎ Π½Π΅ΡΠ΅ ΡΠ²ΡΡΠ»ΠΎ ΡΠ° ΡΠΏΡΠΈΡΡ Π²ΡΠ΄Π½ΠΎΠ²Π»Π΅Π½Π½Ρ ΠΊΡΠ°ΡΠ½ΠΈ.
Π¨ΡΠΊΠ°ΡΠΌΠΎ Middle Data ScientistΡst, Π΄Π»Ρ ΠΏΡΠ΄ΡΠΈΠ»Π΅Π½Π½Ρ Data Science-ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ. Π―ΠΊΠΈΠΉ Π±ΡΠ΄Π΅ Π΄ΠΎΠ»ΡΡΠ΅Π½ΠΈΠΉ Π΄ΠΎ Π²ΠΈΠΊΠΎΠ½Π°Π½Π½Ρ ΠΏΠΎΠ²Π½ΠΎΠ³ΠΎ ΡΠΈΠΊΠ»Ρ ΠΏΡΠΎΠ΅ΠΊΡΡΠ² β Π²ΡΠ΄ Π°Π½Π°Π»ΡΠ·Ρ Π΄Π°Π½ΠΈΡ Π΄ΠΎ Π·Π°ΠΏΡΡΠΊΡ ΠΌΠΎΠ΄Π΅Π»Ρ Ρ ΠΏΡΠΎΠ΄Π°ΠΊΡΠ½, ΠΏΡΠ°ΡΡΡΡΠΈ Ρ ΠΊΡΠΎΡ-ΡΡΠ½ΠΊΡΡΠΎΠ½Π°Π»ΡΠ½ΡΠΉ ΠΊΠΎΠΌΠ°Π½Π΄Ρ.
Π€ΡΠ½ΠΊΡΡΡ ΠΏΠΎΡΠ°Π΄ΠΈ:
- ΠΠ½Π°Π»ΡΠ· ΠΏΡΠΎΠ±Π»Π΅ΠΌΠΈ ΡΠ° ΠΏΠΎΡΡΠ°Π½ΠΎΠ²ΠΊΠ° Π·Π°Π΄Π°ΡΡ
- ΠΠ±ΡΡ, ΠΎΡΠΈΡΠ΅Π½Π½Ρ ΡΠ° ΠΏΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠ° Π΄Π°Π½ΠΈΡ
- ΠΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ ΡΠ° Π΅ΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠΈ
- ΠΠ°Π»ΡΠ΄Π°ΡΡΡ ΡΠ° ΠΏΠΎΡΡΠ½Π΅Π½Π½Ρ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡΠ²
- Π‘ΠΏΡΠ²ΠΏΡΠ°ΡΡ ΡΠ° ΠΊΠΎΠΌΡΠ½ΡΠΊΠ°ΡΡΡ
- ΠΠΎΠ»ΡΠΏΡΠ΅Π½Π½Ρ ΠΏΡΠΎΡΠ΅ΡΡΠ² ΡΠ° ΠΌΠ΅Π½ΡΠΎΡΡΡΠ²ΠΎ
- R&D ΡΠ° ΡΠΎΠ·Π²ΠΈΡΠΎΠΊ Π΅ΠΊΡΠΏΠ΅ΡΡΠΈΠ·ΠΈ
ΠΡΠΎΡΠ΅ΡΡΠΉΠ½Ρ ΠΊΠΎΠΌΠΏΠ΅ΡΠ΅Π½ΡΡΡ:
- ΠΠΌΡΠ½Π½Ρ ΡΡΡΠΊΠΎ ΡΠΎΡΠΌΡΠ»ΡΠ²Π°ΡΠΈ Π·Π°Π΄Π°ΡΡ ΡΠ° ΡΡΠ°Π²ΠΈΡΠΈ ΠΏΠΈΡΠ°Π½Π½Ρ
- ΠΠΌΡΠ½Π½Ρ ΠΏΠΎΠ΄ΠΈΠ²ΠΈΡΠΈΡΡ Π½Π° ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ ΠΏΡΠ΄ ΡΠ½ΡΠΈΠΌ ΠΊΡΡΠΎΠΌ Π·ΠΎΡΡ
- Python (pandas, NumPy, scikit-learn), SQL; Π²ΠΏΠ΅Π²Π½Π΅Π½Π° ΡΠΎΠ±ΠΎΡΠ° Π· Git.
- ΠΠ»Π°ΡΠΈΡΠ½Ρ ML-Π°Π»Π³ΠΎΡΠΈΡΠΌΠΈ (Gradient Boosting β XGBoost/LightGBM/CatBoost, Random Forest, Logistic/Linear Regression, k-NN); Π·Π½Π°Π½Π½Ρ ΠΌΠ΅ΡΠΎΠ΄ΡΠ² ΡΠ΅Π³ΡΠ»ΡΡΠΈΠ·Π°ΡΡΡ, ΠΊΡΠΎΡ-Π²Π°Π»ΡΠ΄Π°ΡΡΡ ΡΠ° ΠΏΡΠ΄Π±ΠΎΡΡ Π³ΡΠΏΠ΅ΡΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΡΠ².
- ΠΠΌΠΎΠ²ΡΡΠ½ΡΡΠ½Ρ ΡΠΎΠ·ΠΏΠΎΠ΄ΡΠ»ΠΈ, ΠΏΠ΅ΡΠ΅Π²ΡΡΠΊΠ° Π³ΡΠΏΠΎΡΠ΅Π·, A/B-ΡΠ΅ΡΡΠΈ, ΡΠ½ΡΠ΅ΠΏΡΠ΅ΡΠΎΠ²Π°Π½ΡΡΡΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ.
- PyTorch Π°Π±ΠΎ TensorFlow/Keras Π΄Π»Ρ Π·Π°Π΄Π°Ρ CV ΡΠΈ NLP; ΡΠΌΡΠ½Π½Ρ Π±ΡΠ΄ΡΠ²Π°ΡΠΈ ΡΠ° ΡΡΠ΅Π½ΡΠ²Π°ΡΠΈ ΠΌΠΎΠ΄Π΅Π»Ρ Π· TensorBoard-Π»ΠΎΠ³ΡΠ²Π°Π½Π½ΡΠΌ.
- MLflow / Weights & Biases, Docker; Π±Π°Π·ΠΎΠ²Π΅ ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ CI/CD Π΄Π»Ρ ML-ΠΏΠ°ΠΉΠΏΠ»Π°ΠΉΠ½ΡΠ².
- ΠΡΠ°ΠΊΡΠΈΡΠ½ΠΈΠΉ Π΄ΠΎΡΠ²ΡΠ΄ Ρ Ρ ΠΎΡΠ° Π± ΠΎΠ΄Π½ΡΠΉ ΡΠ· ΠΏΠ»Π°ΡΡΠΎΡΠΌ (AWS, GCP, Azure) Π΄Π»Ρ ΡΠΎΠ·Π³ΠΎΡΡΠ°Π½Π½Ρ Π°Π±ΠΎ ΡΡΠ΅Π½ΡΠ²Π°Π½Π½Ρ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ.
- ΠΠ°ΡΠ²Π½ΡΡΡΡ ΡΠ΅ΡΡΠΈΡΡΠΊΠ°ΡΡΡ ΠΏΠΎ Data&AI
- ΠΠΌΡΠ½Π½Ρ Π½Π΅Π·Π°Π»Π΅ΠΆΠ½ΠΎ ΠΏΠ΅ΡΠ΅Π²ΡΡΡΡΠΈ Π²Ρ ΡΠ΄Π½Ρ Π΄Π°Π½Ρ ΡΠ° ΡΠ΅Π·ΡΠ»ΡΡΠ°Ρ
- ΠΠ²ΡΠΎΠ½ΠΎΠΌΠ½ΡΡΡΡ
- ΠΠΎΠΌΡΠ½ΡΠΊΠ°Π±Π΅Π»ΡΠ½ΡΡΡΡ
ΠΠΈ ΠΏΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ:
- ΠΡΡΡΡΠΉΠ½Π΅ ΠΏΡΠ°ΡΠ΅Π²Π»Π°ΡΡΡΠ²Π°Π½Π½Ρ
- KΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠ½ΠΈΠΉ ΡΡΠ²Π΅Π½Ρ Π·Π°ΡΠΎΠ±ΡΡΠ½ΠΎΡ ΠΏΠ»Π°ΡΠΈ ΡΠ° ΡΠΎΡΡΠ°Π»ΡΠ½Ρ Π³Π°ΡΠ°Π½ΡΡΡ
- ΠΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½Π° ΠΏΡΠΎΠ³ΡΠ°ΠΌΠ° ΠΌΠ΅Π΄ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΡΠ°Ρ ΡΠ²Π°Π½Π½Ρ ΡΠ° ΠΏΡΠΎΠ³ΡΠ°ΠΌΠ° ΠΏΡΠΈΡ ΠΎΠ»ΠΎΠ³ΡΡΠ½ΠΎΡ ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠΈ ΡΠΏΡΠ²ΡΠΎΠ±ΡΡΠ½ΠΈΠΊΡΠ²
- Π ΠΎΠ±ΠΎΡΡ Π² ΡΠ½Π½ΠΎΠ²Π°ΡΡΠΉΠ½ΠΎΠΌΡ ΠΏΠ°ΡΠΊΡ Unit City
- ΠΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΡ Π½Π°Π²ΡΠ°Π½Π½Ρ ΡΠ° ΠΏΡΠΎΡΠ΅ΡΡΠΉΠ½ΠΈΠΉ ΡΠΎΠ·Π²ΠΈΡΠΎΠΊ (ΠΎΠ½Π»Π°ΠΉΠ½ ΠΊΡΡΡΠΈ, Π°ΡΠ΄ΠΈΡΠΎΡΠ½Ρ ΡΡΠ΅Π½ΡΠ½Π³ΠΈ, ΠΌΠ°ΠΉΡΡΠ΅Ρ-ΠΊΠ»Π°ΡΠΈ, ΠΏΡΠΎΡΠ΅ΡΡΠΉΠ½Ρ ΡΠΏΡΠ»ΡΠ½ΠΎΡΠΈ)
ΠΠΈ ΡΡΠ½ΡΡΠΌΠΎ Π²Π°Ρ ΡΠ½ΡΠ΅ΡΠ΅Ρ Π΄ΠΎ MODUS X ΡΠ° Π³ΠΎΡΠΎΠ²Π½ΡΡΡΡ ΠΏΡΠΈΠΉΠΌΠ°ΡΠΈ Π²ΠΈΠΊΠ»ΠΈΠΊΠΈ. Π’ΡΡ ΠΊΠΎΠΆΠ΅Π½ ΠΌΠΎΠΆΠ΅ ΡΠΎΠ·ΠΊΡΠΈΡΠΈ ΡΠ²ΠΎΡ ΡΠ°Π»Π°Π½ΡΠΈ ΠΉ Π·ΡΠΎΠ±ΠΈΡΠΈ Π²Π½Π΅ΡΠΎΠΊ Ρ ΡΠΏΡΠ»ΡΠ½ΠΈΠΉ ΡΡΠΏΡΡ . ΠΠΈ ΡΠ½Π²Π΅ΡΡΡΡΠΌΠΎ Π² ΡΠΎΠ·Π²ΠΈΡΠΎΠΊ, Π΄ΠΎΠΏΠΎΠΌΠ°Π³Π°ΡΠΌΠΎ ΠΎΡΡΠΈΠΌΡΠ²Π°ΡΠΈ Π½ΠΎΠ²Ρ Π·Π½Π°Π½Π½Ρ ΡΠ° Π΄ΠΎΡΡΠ³Π°ΡΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠΉΠ½ΠΈΡ ΡΡΠ»Π΅ΠΉ.
ΠΠ°ΡΠ° ΠΊΠΎΠΌΠ°Π½Π΄Π° ΡΠ²Π°ΠΆΠ½ΠΎ ΡΠΎΠ·Π³Π»ΡΠ΄Π°Ρ Π²ΡΡ Π·Π°ΡΠ²ΠΊΠΈ, Ρ ΡΠΊΡΠΎ Π²Π°ΡΠ° ΠΊΠ°Π½Π΄ΠΈΠ΄Π°ΡΡΡΠ° Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π°Ρ Π²ΠΈΠΌΠΎΠ³Π°ΠΌ Π²Π°ΠΊΠ°Π½ΡΡΡ, ΡΠ΅ΠΊΡΡΡΠ΅Ρ ΠΎΠ±ΠΎΠ²βΡΠ·ΠΊΠΎΠ²ΠΎ Π·Π²βΡΠΆΠ΅ΡΡΡΡ Π· Π²Π°ΠΌΠΈ Π²ΠΏΡΠΎΠ΄ΠΎΠ²ΠΆ 2 ΡΠΈΠΆΠ½ΡΠ².
ΠΡΠ»ΡΡΠ΅ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΡ ΠΏΡΠΎ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ ΡΠ° Π½Π°Ρ Π΄ΠΎΡΠ²ΡΠ΄ Π½Π° ΠΎΡΡΡΡΠΉΠ½ΡΠΉ ΡΡΠΎΡΡΠ½ΡΡ MODUS X Π² LinkedIn.
ΠΠ°ΠΏΡΠ°Π²Π»ΡΡΡΠΈ ΡΠ΅Π·ΡΠΌΠ΅ Π½Π° ΡΡ Π²Π°ΠΊΠ°Π½ΡΡΡ, ΠΠΈ Π½Π°Π΄Π°ΡΡΠ΅ Π·Π³ΠΎΠ΄Ρ Π’ΠΠ Β«ΠΠΠΠ£Π‘ ΠΠΠ‘Β» Π½Π° ΠΎΠ±ΡΠΎΠ±ΠΊΡ Π½Π°Π΄Π°Π½ΠΈΡ ΠΠ°ΠΌΠΈ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ Π·Π³ΡΠ΄Π½ΠΎ ΠΠ°ΠΊΠΎΠ½Ρ Π£ΠΊΡΠ°ΡΠ½ΠΈ Β«ΠΡΠΎ Π·Π°Ρ ΠΈΡΡ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ Β». ΠΠ³ΠΎΠ΄Π° Π½Π°Π΄Π°ΡΡΡΡΡ Π² ΡΠΎΠΌΡ ΡΠΈΡΠ»Ρ Π΄Π»Ρ ΡΡ ΠΎΠ±ΡΠΎΠ±ΠΊΠΈ Π² Π·ΠΎΠ²Π½ΡΡΠ½ΡΡ ΡΠΈΡΡΠ΅ΠΌΠ°Ρ , Π· ΠΌΠ΅ΡΠΎΡ ΡΡΠΏΡΠΎΠ²ΠΎΠ΄ΠΆΠ΅Π½Π½Ρ ΠΏΡΠΎΡΠ΅ΡΡ Π½Π°ΠΉΠΌΡ.
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Middle Data Scientist
Full Remote Β· Ukraine Β· Product Β· 3 years of experienceΠ’ΠΠ Β«ΠΠ‘ Π‘ΠΠ’ΠΒ» β ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠ° ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ, ΡΠΎ ΡΠΏΠ΅ΡΡΠ°Π»ΡΠ·ΡΡΡΡΡΡ Π½Π° ΡΡΠ²ΠΎΡΠ΅Π½Π½Ρ ΡΠ½Π½ΠΎΠ²Π°ΡΡΠΉΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠ½ΠΎΠ³ΠΎ Π·Π°Π±Π΅Π·ΠΏΠ΅ΡΠ΅Π½Π½Ρ Π΄Π»Ρ ΡΠΈΡΠ΅ΠΉΠ»-ΡΠ΅ΠΊΡΠΎΡΡ, ΡΠΎΠ·ΡΠΎΠ±Π»ΡΡΡΠΈ ΡΡΡΠ΅Π½Π½Ρ, ΡΠΊΡ ΠΌΠ°ΠΊΡΠΈΠΌΠ°Π»ΡΠ½ΠΎ Π·Π°Π΄ΠΎΠ²ΠΎΠ»ΡΠ½ΡΡΡΡ ΠΏΠΎΡΡΠ΅Π±ΠΈ ΠΊΠ»ΡΡΠ½ΡΡΠ². ΠΠ°ΡΡ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ ΡΠΎΠ΄Π½Ρ Π΄ΠΎΠ²ΠΎΠ΄ΡΡΡ ΡΠ²ΠΎΡ Π½Π°Π΄ΡΠΉΠ½ΡΡΡΡ Ρ...Π’ΠΠ Β«ΠΠ‘ Π‘ΠΠ’ΠΒ» β ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠ° ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ, ΡΠΎ ΡΠΏΠ΅ΡΡΠ°Π»ΡΠ·ΡΡΡΡΡΡ Π½Π° ΡΡΠ²ΠΎΡΠ΅Π½Π½Ρ ΡΠ½Π½ΠΎΠ²Π°ΡΡΠΉΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠ½ΠΎΠ³ΠΎ Π·Π°Π±Π΅Π·ΠΏΠ΅ΡΠ΅Π½Π½Ρ Π΄Π»Ρ ΡΠΈΡΠ΅ΠΉΠ»-ΡΠ΅ΠΊΡΠΎΡΡ, ΡΠΎΠ·ΡΠΎΠ±Π»ΡΡΡΠΈ ΡΡΡΠ΅Π½Π½Ρ, ΡΠΊΡ ΠΌΠ°ΠΊΡΠΈΠΌΠ°Π»ΡΠ½ΠΎ Π·Π°Π΄ΠΎΠ²ΠΎΠ»ΡΠ½ΡΡΡΡ ΠΏΠΎΡΡΠ΅Π±ΠΈ ΠΊΠ»ΡΡΠ½ΡΡΠ².
ΠΠ°ΡΡ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ ΡΠΎΠ΄Π½Ρ Π΄ΠΎΠ²ΠΎΠ΄ΡΡΡ ΡΠ²ΠΎΡ Π½Π°Π΄ΡΠΉΠ½ΡΡΡΡ Ρ Π΅ΡΠ΅ΠΊΡΠΈΠ²Π½ΡΡΡΡ Ρ ΡΠ΅Π°Π»ΡΠ½ΠΈΡ ΡΠΌΠΎΠ²Π°Ρ ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠΎΠ³ΠΎ ΡΠΈΡΠ΅ΠΉΠ»Ρ.
ΠΠΈ ΡΡΠΊΠ°ΡΠΌΠΎ Ρ Π½Π°ΡΡ ΠΊΠΎΠΌΠ°Π½Π΄Ρ Middle Data Scientist.
ΠΠ»Ρ Π½Π°Ρ Π²Π°ΠΆΠ»ΠΈΠ²ΠΎ:
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π½Π° Π°Π½Π°Π»ΠΎΠ³ΡΡΠ½ΡΠΉ ΠΏΠΎΡΠ°Π΄Ρ Π²ΡΠ΄ 3-Ρ ΡΠΎΠΊΡΠ²
- ΠΠ½Π°Π½Π½Ρ Python ΡΠ° SQL
- ΠΠ½Π°Π½Π½Ρ Π±ΡΠ±Π»ΡΠΎΡΠ΅ΠΊ: pandas, numpy, pyplot, scikit-learn, tensorflow, cuda, PyTorch
- Π ΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΡΠΏΠ΅ΡΠΈΡΡΠΊΠΈ Π΄Π°Π½ΠΈΡ Ρ ΠΊΠΎΠ½ΡΠ΅ΠΊΡΡΡ Π±ΡΠ·Π½Π΅ΡΡ (ΡΠ΅Π·ΠΎΠ½Π½ΡΡΡΡ, ΡΠ΅Π³ΡΠΎΠ½Π°Π»ΡΠ½Ρ ΠΎΡΠΎΠ±Π»ΠΈΠ²ΠΎΡΡΡ, ΠΏΠΎΠ²Π΅Π΄ΡΠ½ΠΊΠΎΠ²Ρ ΠΏΠ°ΡΠ΅ΡΠ½ΠΈ ΠΊΠ»ΡΡΠ½ΡΡΠ²)
- ΠΡΠ°ΠΊΡΠΈΡΠ½ΠΈΠΉ Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· ΠΌΠΎΠ΄Π΅Π»ΡΠΌΠΈ: ΠΊΠ»Π°ΡΠΈΡΡΠΊΠ°ΡΡΡ, ΡΠ΅Π³ΡΠ΅ΡΡΡ, ΠΊΠ»Π°ΡΡΠ΅ΡΠΈΠ·Π°ΡΡΡ; Π΄Π΅ΡΠ΅Π² ΡΡΡΠ΅Π½Ρ, Π°Π½ΡΠ°ΠΌΠ±Π»ΡΠ² (Random Forest, XGBoost); Π½Π΅ΠΉΡΠΎΠ½Π½ΠΈΡ ΠΌΠ΅ΡΠ΅ΠΆ (Π±Π°Π·ΠΎΠ²ΠΈΠΉ ΡΡΠ²Π΅Π½Ρ)
- ΠΠ½Π°Π½Π½Ρ ΠΌΠ΅ΡΡΠΈΠΊ ΡΠΊΠΎΡΡΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΡΠ° Π²ΠΌΡΠ½Π½Ρ ΡΡ ΡΠ½ΡΠ΅ΡΠΏΡΠ΅ΡΡΠ²Π°ΡΠΈ
- Π ΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΡΠ΅ΠΎΡΡΡ ΠΉΠΌΠΎΠ²ΡΡΠ½ΠΎΡΡΠ΅ΠΉ, ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ½ΠΎΡ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ, Π»ΡΠ½ΡΠΉΠ½ΠΎΡ Π°Π»Π³Π΅Π±ΡΠΈ ΡΠ° ΡΠΈΡΠ΅Π»ΡΠ½ΠΈΡ ΠΌΠ΅ΡΠΎΠ΄ΡΠ²
- ΠΠΌΡΠ½Π½Ρ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΡΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ½ΠΈΠΉ Π°Π½Π°Π»ΡΠ· (Π³ΡΠΏΠΎΡΠ΅Π·ΠΈ, ΡΠ΅ΡΡΡΠ²Π°Π½Π½Ρ, ΠΊΠΎΡΠ΅Π»ΡΡΡΡ)
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· Ρ ΠΌΠ°ΡΠ½ΠΈΠΌΠΈ ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΠΌΠΈ Π±ΡΠ΄Π΅ ΠΏΠ»ΡΡΠΎΠΌ
ΠΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π°Π»ΡΠ½Π΅ ΡΠ° ΡΠ΅ΡΠΉΠΎΠ·Π½Π΅ ΡΡΠ°Π²Π»Π΅Π½Π½Ρ Π΄ΠΎ ΡΠΎΠ±ΠΎΡΠΈ
Π£ Π½Π°ΡΡΠΉ ΠΊΠΎΠΌΠ°Π½Π΄Ρ ΡΠΈ Π±ΡΠ΄Π΅Ρ:
- ΠΠ±ΠΈΡΠ°ΡΠΈ ΡΡΡΠΎΡΠΈΡΠ½Ρ Π΄Π°Π½Ρ ΠΏΡΠΎ ΠΏΡΠΎΠ΄Π°ΠΆΡ, ΡΡΠ½ΠΈ, Π·Π°ΠΏΠ°ΡΠΈ, ΠΌΠ°ΡΠΊΠ΅ΡΠΈΠ½Π³ΠΎΠ²Ρ Π°ΠΊΡΠΈΠ²Π½ΡΡΡΡ, ΡΠ΅Π·ΠΎΠ½Π½ΡΡΡΡ, ΠΏΡΠΎΠΌΠΎΠ°ΠΊΡΡΡ, ΠΏΠΎΠ³ΠΎΠ΄Ρ, ΠΏΠΎΠ΄ΡΡ ΡΠΎΡΠΎ
- ΠΠ΄ΡΠΉΡΠ½ΡΠ²Π°ΡΠΈ ΠΏΠΎΠΏΠ΅ΡΠ΅Π΄Π½Ρ ΠΎΠ±ΡΠΎΠ±ΠΊΡ: ΠΎΡΠΈΡΠ΅Π½Π½Ρ, Π·Π°ΠΏΠΎΠ²Π½Π΅Π½Π½Ρ ΠΏΡΠΎΠΏΡΡΠΊΡΠ², ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΡΡ, Π½ΠΎΡΠΌΠ°Π»ΡΠ·Π°ΡΡΡ Π΄Π°Π½ΠΈΡ
- ΠΡΠΎΠ²ΠΎΠ΄ΠΈΡΠΈ EDA (exploratory data analysis) Π΄Π»Ρ Π²ΠΈΡΠ²Π»Π΅Π½Π½Ρ Π·Π°ΠΊΠΎΠ½ΠΎΠΌΡΡΠ½ΠΎΡΡΠ΅ΠΉ Ρ ΠΏΠΎΠΏΠΈΡΡ
- Π‘ΡΠ²ΠΎΡΡΠ²Π°ΡΠΈ ΡΠ° ΡΡΠ΅Π½ΡΠ²Π°ΡΠΈ ΠΌΠΎΠ΄Π΅Π»Ρ ΡΠ°ΡΠΎΠ²ΠΈΡ ΡΡΠ΄ΡΠ² (ARIMA, SARIMA ΡΠΎΡΠΎ) ΡΠ°/Π°Π±ΠΎ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ (XGBoost, Random Forest)
- ΠΡΠ°ΡΡΠ²Π°ΡΠΈ Π· ΡΡΡΠ΅ΡΠ½ΠΆΠΈΠ½ΡΡΠΈΠ½Π³ΠΎΠΌ Π΄Π»Ρ ΠΏΠΎΠΊΡΠ°ΡΠ΅Π½Π½Ρ ΡΠΎΡΠ½ΠΎΡΡΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ
- ΠΠΎΡΡΠ²Π½ΡΠ²Π°ΡΠΈ ΡΠΎΡΠ½ΠΎΡΡΡ ΡΡΠ·Π½ΠΈΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΡΠ° ΠΎΠ±ΠΈΡΠ°ΡΠΈ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΠΈΠΉ ΠΏΡΠ΄Ρ ΡΠ΄
- ΠΠ΄ΡΠΉΡΠ½ΡΠ²Π°ΡΠΈ Π½Π°Π»Π°ΡΡΡΠ²Π°Π½Π½Ρ ΠΌΠ΅ΡΡΠΈΠΊ ΡΠΊΠΎΡΡΡ (MAPE, RMSE, WAPE, sMAPE ΡΠΎΡΠΎ)
- Π ΠΎΠ·ΡΠΎΠ±Π»ΡΡΠΈ Π±Π°Π·ΠΎΠ²Ρ ΡΠ° Π°Π½ΡΠ°ΠΌΠ±Π»Π΅Π²Ρ ΠΌΠΎΠ΄Π΅Π»Ρ, ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΡΠΈ A/B-ΡΠ΅ΡΡΠΈ ΠΏΡΠΈ Π½Π΅ΠΎΠ±Ρ ΡΠ΄Π½ΠΎΡΡΡ
- ΠΠ΄ΡΠΉΡΠ½ΡΠ²Π°ΡΠΈ Π²Π°Π»ΡΠ΄Π°ΡΡΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π½Π° ΡΠ΅ΡΡΠΎΠ²ΠΈΡ Π²ΠΈΠ±ΡΡΠΊΠ°Ρ
- ΠΡΠΎΠ²ΠΎΠ΄ΠΈΡΠΈ ΠΏΠ΅ΡΠ΅ΡΡΠ΅Π½ΡΠ²Π°Π½Π½Ρ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Ρ ΡΠ°Π·Ρ Π·ΠΌΡΠ½ Π² ΡΠΈΠ½ΠΊΠΎΠ²ΠΎΠΌΡ ΡΠ΅ΡΠ΅Π΄ΠΎΠ²ΠΈΡΡ
- Π ΠΎΠ·ΡΠΎΠ±Π»ΡΡΠΈ ΡΠΈΡΡΠ΅ΠΌΠΈ ΡΠΏΠΎΠ²ΡΡΠ΅Π½Π½Ρ ΠΏΡΠΈ Π·Π½ΠΈΠΆΠ΅Π½Π½Ρ ΡΠΎΡΠ½ΠΎΡΡΡ
ΠΡΠΎΠ²ΠΎΠ΄ΠΈΡΠΈ ΠΏΠΎΡΡΡΠΉΠ½ΠΈΠΉ ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³ ΡΠΊΠΎΡΡΡ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΡΠ²
ΠΠΈ ΠΏΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ:
- Π¨ΠΈΡΠΎΠΊΡ ΠΌΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΡ Π΄Π»Ρ ΠΏΡΠΎΡΠ΅ΡΡΠΉΠ½ΠΎΠ³ΠΎ ΡΠΎΠ·Π²ΠΈΡΠΊΡ ΡΠ° ΡΡΠΊΠ°Π²Ρ ΠΏΡΠΎΡΠΊΡΠΈ
- ΠΡΠ΄Π½Ρ ΡΠ° ΡΠ²ΠΎΡΡΠ°ΡΠ½Ρ Π²ΠΈΠΏΠ»Π°ΡΡ ΡΡΠ½Π°Π½ΡΠΎΠ²ΠΎΡ Π²ΠΈΠ½Π°Π³ΠΎΡΠΎΠ΄ΠΈ
- ΠΡΠ΄Π΄Π°Π»Π΅Π½ΠΈΠΉ Π°Π±ΠΎ Π³ΡΠ±ΡΠΈΠ΄Π½ΠΈΠΉ Π³ΡΠ°ΡΡΠΊ ΡΠΎΠ±ΠΎΡΠΈ (Ρ Π² ΠΎΡΡΡΡ, Ρ Π΄ΠΈΡΡΠ°Π½ΡΡΠΉΠ½ΠΎ): Π· 9:00 Π΄ΠΎ 18:00
- ΠΠ΅Π΄ΠΈΡΠ½Π΅ ΡΡΡΠ°Ρ ΡΠ²Π°Π½Π½Ρ ΡΠ° Π²ΠΈΠ³ΡΠ΄Π½Ρ ΡΠΌΠΎΠ²ΠΈ Π΄Π»Ρ ΡΡΡΠ°Ρ ΡΠ²Π°Π½Π½Ρ ΡΠΎΠ΄ΠΈΡΡΠ² Ρ Π΄ΡΡΠ΅ΠΉ
- ΠΡΠ΄Π½ΠΎΠ²Π»Π΅Π½Ρ Π²ΠΈΡ ΡΠ΄Π½Ρ Ρ Π΄Π΅ΡΠΆΠ°Π²Π½Ρ ΡΠ²ΡΡΠ°
- ΠΠ½ΠΈΠΆΠΊΠΈ ΡΠ° Π΄ΠΎΠ΄Π°ΡΠΊΠΎΠ²Ρ ΡΡΡΠΊΠΈ Π²ΡΠ΄ ΠΏΠ°ΡΡΠ½Π΅ΡΡΠ²
ΠΠΎΠΌΡΠΎΡΡΠ½Ρ ΡΠΌΠΎΠ²ΠΈ ΠΏΡΠ°ΡΡ (ΠΎΡΡΡ Π½Π° ΠΏΡΠ°Π²ΠΎΠΌΡ Π±Π΅ΡΠ΅Π·Ρ ΠΠΈΡΠ²Π° β ΡΠ°ΠΉΠΎΠ½ ΡΡΠ°Π½ΡΡΡ ΠΌΠ΅ΡΡΠΎ ΠΠΎΠ½ΡΡΠ°ΠΊΡΠΎΠ²Π° ΠΏΠ»ΠΎΡΠ°)
Π§Π΅ΠΊΠ°ΡΠΌΠΎ Π½Π° ΡΠ²ΠΎΡ ΡΠ΅Π·ΡΠΌΠ΅!
ΠΠΈ ΡΠΎΠ·Π³Π»ΡΠ΄Π°ΡΠΌΠΎ Π²ΡΠ΄Π³ΡΠΊΠΈ ΠΏΡΠΎΡΡΠ³ΠΎΠΌ 5 ΡΠΎΠ±ΠΎΡΠΈΡ Π΄Π½ΡΠ². Π―ΠΊΡΠΎ Π½Π΅ ΠΎΡΡΠΈΠΌΠ°ΡΡ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Ρ Π²ΠΏΡΠΎΠ΄ΠΎΠ²ΠΆ ΡΡΠΎΠ³ΠΎ ΡΠ°ΡΡ, ΡΠ΅ ΠΎΠ·Π½Π°ΡΠ°Ρ, ΡΠΎ Π½Π°ΡΠ°Π·Ρ ΠΌΠΈ Π½Π΅ ΠΌΠΎΠΆΠ΅ΠΌΠΎ Π·Π°ΠΏΡΠΎΠΏΠΎΠ½ΡΠ²Π°ΡΠΈ ΠΏΠΎΠ·ΠΈΡΡΡ, Π°Π»Π΅ ΠΌΠΈ Π·Π±Π΅ΡΠ΅Π³Π»ΠΈ ΡΠ΅Π·ΡΠΌΠ΅ Ρ Π½Π°ΡΡΠΉ Π±Π°Π·Ρ.
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