Jobs

56
  • Β· 24 views Β· 5 applications Β· 7d

    Azure Data/ Machine Learning Expert (Microsoft Certified DP-100 / DP-203)

    Full Remote Β· Countries of Europe or Ukraine Β· 3 years of experience Β· Intermediate
    We’re building a team of certified data professionals to work on high-impact projects in the areas of data engineering and machine learning using Microsoft Azure. If you are certified in one or more of the following areas, let’s connect! Required...

    We’re building a team of certified data professionals to work on high-impact projects in the areas of data engineering and machine learning using Microsoft Azure. If you are certified in one or more of the following areas, let’s connect!

     

    Required Certifications:

    • DP-100 – Microsoft Certified: Azure Data Scientist Associate
    • DP-203 – Microsoft Certified: Azure Data Engineer Associate

     

    What you'll be doing:

    • Designing and developing data pipelines and ML models on Azure
    • Working with large datasets and building scalable solutions
    • Collaborating with engineering and business teams to implement end-to-end data solutions
    • Supporting proof of concept and prototype development

     

    What we expect:

    • Valid certification(s) in DP-100 or DP-203
    • Practical experience with Azure Machine Learning, Synapse, Data Factory, or related tools
    • Strong analytical skills and understanding of data modeling and ML workflows
    • English – Intermediate level or higher
    More
  • Β· 23 views Β· 4 applications Β· 6d

    Senior Data Scientist

    Full Remote Β· EU Β· 5 years of experience Β· Upper-Intermediate
    UVIK Software is looking for an experienced and proactive Senior Data Scientist to join our team. You will take ownership of end-to-end machine learning solutions β€” from exploration to deployment β€” and turn complex business challenges into actionable...

    UVIK Software is looking for an experienced and proactive Senior Data Scientist to join our team. You will take ownership of end-to-end machine learning solutions β€” from exploration to deployment β€” and turn complex business challenges into actionable insights. This role is perfect for someone who thrives in a fast-paced, data-driven environment and wants to make real impact through intelligent systems.
     

    What You’ll Do:

    • Design, develop, and deploy machine learning models using structured and unstructured data
    • Own the full ML lifecycle: data exploration, feature engineering, model training, evaluation, deployment, and monitoring
    • Use Apache Spark (PySpark) to efficiently process large-scale datasets in distributed environments
    • Collaborate with data engineers, product managers, and stakeholders to align ML models with business goals
    • Perform model validation and performance tuning, ensuring reproducibility with robust pipelines
    • Work in Python with libraries such as pandas, scikit-learn, NumPy, MLflow
    • Use Git for version control and collaborate via code reviews and structured workflows
    • Present insights, recommendations, and results clearly to both technical and non-technical audiences
    • Stay up to date with AI/ML trends and assess new tools and techniques for implementation
    • Document models, experiments, and workflows for clarity and future use
       

    What We’re Looking For:

    • 5+ years of experience in machine learning, AI, and statistical modeling
    • Deep expertise in supervised, unsupervised, and ensemble learning methods
    • Strong proficiency in Python for data science and machine learning
    • Hands-on experience with Apache Spark / PySpark for distributed data processing
    • Solid knowledge of Git and collaborative development practices
    • Experience building scalable, production-grade ML pipelines and working with large datasets
    • Strong problem-solving skills and solid foundations in math and statistics
    • Excellent communication skills β€” ability to explain technical results to non-technical audiences
    • Based in an EU country
       

    Nice to Have

    • Experience with cloud-based ML platforms like AWS SageMaker, GCP, or Azure ML
    More
  • Β· 16 views Β· 0 applications Β· 6d

    Senior Data Science/ AI Engineer (with Databricks)

    Poland Β· 4 years of experience Β· Upper-Intermediate
    The Company (Location: Langenfeld, Germany): Since 2002, the client has been a market leader in automotive claims management, processing over 18 million vehicle claims annually with a global team of more than 2,000 employees. Operating in over 30...

    The Company (Location: Langenfeld, Germany):
    Since 2002, the client has been a market leader in automotive claims management, processing over 18 million vehicle claims annually with a global team of more than 2,000 employees. Operating in over 30 countries, the company specializes in digital solutions that optimize vehicle damage processing for insurance companies, car dealerships, repair shops, leasing firms, and automotive manufacturers. By leveraging automation, advanced technologies, and industry expertise, the client continuously enhances efficiency and accuracy in claims handling. An in-house research and development team drives innovation, tailoring solutions to local market needs while advancing digital transformation in the industry. At the core of this evolution is a strong development team, building scalable, high-performance software solutions that integrate data-driven processes with human expertise to reshape automotive claims management.

    Short Role Description: We are seeking a Senior Data Scientist / AI Engineer with expertise in Databricks to enhance our capabilities in developing advanced AI solutions for automotive claims management. You will leverage your analytical and machine learning skills to innovate and improve data-driven processes, working closely with data engineers and solution architects in a collaborative, international environment.

    Key Responsibilities:

    • Develop and implement advanced machine learning and AI models using Databricks.
    • Collaborate with data engineering and solution architecture teams to define and refine data processing pipelines.
    • Analyze complex datasets (structured, PDFs, images) to extract meaningful insights and predictive capabilities.
    • Build and maintain vector databases, leveraging embeddings and AI model integrations.
    • Actively participate in AI governance, ensuring best practices in model development, validation, and deployment.
    • Document methodologies, experiments, and model architectures for reproducibility and knowledge sharing.
    • Continuously evaluate emerging technologies and methodologies in AI to enhance capabilities.
    • Present findings clearly and persuasively to technical and non-technical stakeholders.

    What We Expect from You (Requirements):

    • 4+ years of proven experience in Data Science or AI Engineering.
    • Strong expertise in developing and deploying machine learning models using Databricks.
    • Proficiency in Python, including common machine learning libraries (TensorFlow, PyTorch, scikit-learn).
    • Familiarity with data handling in cloud environments (Azure or AWS).
    • Solid experience with big data processing frameworks, especially Apache Spark.
    • Experience in managing structured and unstructured data (PDFs, images, hierarchical data).
    • Ability to build, validate, and deploy AI models efficiently and effectively.
    • Strong communication skills, able to present complex data insights clearly.
    • Fluent in English at B2 level or higher.
    • Collaborative, adaptable, and eager to learn within international teams.

    Nice to have:

    • Familiarity with Elasticsearch or other vector-based storage solutions.
    • Experience with NLP and computer vision techniques.
    • Proficiency with container technologies (Docker, Kubernetes).
    • Knowledge of data governance practices related to AI models.
    • Availability for international travel twice a year for workshops and alignment meetings.
    More
  • Β· 17 views Β· 0 applications Β· 6d

    Senior Data Science Engineer

    Poland Β· 4 years of experience Β· Upper-Intermediate
    We are looking for a Data Scientist with a strong analytical mindset and a passion for solving real-world supply chain problems. You will join a cross-functional team focused on optimizing the flow of units from warehouses to stores. This is a high-impact...

    We are looking for a Data Scientist with a strong analytical mindset and a passion for solving real-world supply chain problems. You will join a cross-functional team focused on optimizing the flow of units from warehouses to stores. This is a high-impact role where your insights and models will directly influence key business operations.

    Responsibilities:

    • Prepare and clean datasets to enable reliable experimentation
    • Develop and fine-tune machine learning models and algorithms
    • Test models, analyze outcomes, and generate actionable insights
    • Communicate findings to stakeholders through reports and visualizations
    • Propose data-driven solutions and optimization strategies

    Requirements:

    • Proficiency in Python and/or R
    • Experience with SQL
    • Data Platforms & Tools
    • Hands-on experience with Azure Databricks or Snowflake
    • Familiarity with building and deploying machine learning pipelines is a strong advantage
    • Java experience is a plus
    • Education - Bachelor's or Master's degree in Computer Science, Mathematics, Engineering, or a related field

    Mathematics & Statistics:

    • Solid understanding of multivariable calculus and linear algebra
    • Applied knowledge of statistical distributions and hypothesis testing
    • Machine Learning
    • Practical knowledge of ML techniques: kNN, decision forests, regressions, MLE, time series
    • Understanding of model evaluation metrics and performance tuning
    • Data Handling & Visualization
    • Skilled in managing missing or inconsistent data
    • Experience with tools like matplotlib, seaborn, or ggplot2

    Nice to Have:

    • Experience with deploying ML models into production environments
    • Previous work in supply chain or logistics domains
    More
  • Β· 78 views Β· 3 applications Β· 6d

    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.

    More
  • Β· 18 views Β· 0 applications Β· 5d

    Senior Data Science with Snowflake

    Full Remote Β· Ukraine Β· 5 years of experience Β· Upper-Intermediate
    We are looking for Experienced Senior Data Analyst with Snowflake for one of our projects. About Project: The company is a multinational pharmaceutical and diagnostics corporation. It is renowned for its contributions to healthcare through the...

    We are looking for Experienced Senior Data Analyst with Snowflake for one of our projects. 

    About Project:
    The company is a multinational pharmaceutical and diagnostics corporation. It is renowned for its contributions to healthcare through the development of innovative drugs and diagnostic solutions. With a focus on advancing medical science, the company has established itself as a leader in the biotechnology and healthcare industries. The company commitment to scientific research and development underscores its role in shaping the future of healthcare worldwide.
     

    Responsibilities:
     

    • You will collaborate with cross-functional teams to analyze requirements, develop technical specifications and implement solutions;
    • Analyze large and complex datasets to uncover insights, trends, and patterns that support strategic and operational decision-making
    • Design and maintain dashboards and reports using BI tools (e.g., Power BI, Tableau, or similar) to communicate findings effectively to both technical and non-technical users
    • Act as a bridge between business and technical teams β€” translating business questions into analytical tasks and ensuring data solutions align with business objectives
    • Design and develop data models and data warehouses in Snowflake;
    • Develop and maintain ETL processes to move data from source systems to Snowflake;
    • Create and maintain views, stored procedures, and other database objects.
       

      Requirements:

    •  Proven experience as Data Analyst with Snowflake in a senior capacity;
    • In-depth understanding of Snowflake architecture and best practices;
    • Hands-on experience with AWS;
    • Strong proficiency in SQL and experience working with large datasets;
    • Hands-on experience with data modeling, ETL processes, and data warehousing;
    • Solid understanding of data visualization tools.
    More
  • Β· 54 views Β· 2 applications Β· 4d

    Computer Vision Engineer

    Ukraine Β· Product Β· 4 years of experience MilTech πŸͺ–
    We are looking for a Computer Vision Engineer with a background in classical computer vision techniques and hands-on implementation of low-level CV algorithms. The ideal candidate will have experience with SLAM, Visual-Inertial Odometry (VIO), and sensor...

    We are looking for a Computer Vision Engineer with a background in classical computer vision techniques and hands-on implementation of low-level CV algorithms.

    The ideal candidate will have experience with SLAM, Visual-Inertial Odometry (VIO), and sensor fusion.

    We consider engineers at Middle/Senior levels β€” tasks and responsibilities will be adjusted accordingly.

     

    Required Qualifications:

    • 3+ years of hands-on experience with classical computer vision
    • Knowledge of popular computer vision networks and components 
    • Understanding of geometrical computer vision principles
    • Hands-on experience in implementing low-level CV algorithms
    • Practical experience with SLAM and/or Visual-Inertial Odometry (VIO)
    • Proficiency in C++
    • Experience with Linux
    • Ability to quickly navigate through recent research and trends in computer vision.

    Nice to Have:

    • Experience with Python
    • Familiarity with neural networks and common CV frameworks/libraries (OpenCV, NumPy, PyTorch, ONNX, Eigen, etc.)
    • Experience with sensor fusion.
    More
  • Β· 45 views Β· 14 applications Β· 4d

    Principal/Senior Marketing Analyst to $6000

    Full Remote Β· Worldwide Β· Product Β· 3 years of experience Β· Upper-Intermediate
    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...

    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?

    • 🌍 Fully Remote – Work from anywhere in the world
    • πŸ’° Competitive Pay & Benefits
    • 🌱 Growth Opportunities – International exposure & cross-functional collaboration
    • βš™οΈ Modern Tech Stack – Access to the latest AI models and marketing tools
    • 🀝 Global Team – Work with top-tier talent across continents
    • 🧠 Real Ownership – Make a visible impact on our product and business

       

    Join Us in Building the Future of AI-Powered Consumer Apps

    If you’re passionate about scaling mobile apps through performance marketing and want to work with a dynamic, international team, we want to hear from you!

     

     

     

    More
  • Β· 18 views Β· 0 applications Β· 10h

    Senior Data Scientist to $8000

    Full Remote Β· Bulgaria, Poland, Portugal, Ukraine Β· Product Β· 5 years of experience Β· Upper-Intermediate
    Who we are: Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries. About the Product: Our client is a leading SaaS company offering pricing...

    Who we are:

    Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries. 

     

    About the Product:

    Our client is a leading SaaS company offering pricing optimization solutions for e-commerce businesses. Its advanced technology utilizes big data, machine learning, and AI to assist customers in optimizing their pricing strategies and maximizing their profits.

     

    About the Role:

    As a Data Scientist you’ll play a critical role in shaping and enhancing our AI-driven pricing platform. 

     

    Key Responsibilities:

    • Develop and Optimize Advanced ML Models: Build, improve, and deploy machine learning and statistical models for forecasting demand, analyzing price elasticities, and recommending optimal pricing strategies.
    • Lead End-to-End Data Science Projects: Own your projects fully, from conceptualization and experimentation through production deployment, monitoring, and iterative improvement.
    • Innovate with Generative and Predictive AI Solutions: Leverage state-of-the-art generative and predictive modeling techniques to automate complex pricing scenarios and adapt to rapidly changing market dynamics.

    Required Competence and Skills:

    • A Master’s or PhD in Computer Science, Physics, Applied Mathematics or a related field, demonstrating a strong foundation in analytical thinking.
    • At least 5 years of professional experience in end-to-end machine learning lifecycle (design, development, deployment, and monitoring).
    • At least 5 years of professional experience with Python development, including OOP, writing production-grade code, testing, and optimization.
    • At least 5 years of experience with data mining, statistical analysis, and effective data visualization techniques.
    • Deep familiarity with modern ML/DL methods and frameworks (e.g., PyTorch, XGBoost, scikit-learn, statsmodels).
    • Strong analytical skills combined with practical experience interpreting model outputs to drive business decisions.

    Nice-to-Have:

    • Practical knowledge of SQL and experience with large-scale data systems like Hadoop or Spark.
    • Familiarity with MLOps tools and practices (CI/CD, model monitoring, data version control).
    • Experience in reinforcement learning and Monte-Carlo methods.
    • A solid grasp of microeconomic principles, including supply and demand dynamics, price elasticity, as well as econometrics.
    • Experience with cloud services and platforms, preferably AWS.


     

    More
  • Β· 18 views Β· 0 applications Β· 10h

    Machine Learning Engineer

    Full Remote Β· Ukraine Β· Product Β· 2 years of experience
    Big product software company is looking for a Machine Learning Engineer. Remote work, high salary + financial bonuses (up to 100% of the salary), regular salary review, interesting projects, good working conditions. REQUIREMENTS: - Machine Learning...

    Big product software company is looking for a Machine Learning Engineer. Remote work, high salary + financial bonuses (up to 100% of the salary), regular salary review, interesting projects, good working conditions.

     

    REQUIREMENTS:

    - Machine Learning experience from 2 years;

    - Practical skills with Python;

    - Higher education;

    - Technical English (higher level is advantage).

     

    COMPANY OFFERS:

    - Employment under gig-contract, all taxes are paid;

    - Flexible working hours;

    - 28 days of paid vacation + 15 days at your own expense;

    - Paid sick leave;

    - Medical insurance (with dentistry and optics), including the children;

    - Opportunity to become an inventor of international patents with paid bonuses;

    - Career and professional growth;

    - Own base of courses and trainings;

    - Office in the Kyiv city centre / remotely;

    - Provision of necessary up-to-date equipment;

    - Regular salary review and financial bonuses (up to 100% of the salary);

    - Bonuses for wedding, birth of children and other significant events;

    - Paid maternity leave;

    - Paid lunches, tea, coffee, water, snacks;

    - Discounts to company's products, services.

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  • Β· 13 views Β· 0 applications Β· 3h

    Fractional Mathematician

    Part-time Β· Full Remote Β· Worldwide Β· 3 years of experience Β· Upper-Intermediate
    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...

    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.

    More
  • Β· 28 views Β· 0 applications Β· 3d

    Senior Data Scientist (AI)

    Ukraine Β· Product Β· 5 years of experience Ukrainian Product πŸ‡ΊπŸ‡¦
    Π’ ΠΊΠΎΠΌΠ°Π½Π΄Ρƒ DataDiscovery ΡˆΡƒΠΊΠ°Ρ”ΠΌΠΎ Π½Π° Ρ€ΠΎΠ·ΡˆΠΈΡ€Π΅Π½Π½Ρ Senior Data Scientist. Наш Ρ–Π΄Π΅Π°Π»ΡŒΠ½ΠΈΠΉ ΠΊΠ°Π½Π΄ΠΈΠ΄Π°Ρ‚ ΠΌΠ°Ρ”: - 5+ Ρ€ΠΎΠΊΠΈ ΠΊΠΎΠΌΠ΅Ρ€Ρ†Ρ–ΠΉΠ½ΠΎΠ³ΠΎ досвіду Ρ€ΠΎΠ·Ρ€ΠΎΠ±ΠΊΠΈ. Навички: - Python Ρ‚Π° Π±Ρ–Π±Π»Ρ–ΠΎΡ‚Π΅ΠΊΠΈ машинного навчання: TensorFlow, PyTorch; - Π’Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³Ρ–Ρ— Big Data: Kafka, Amazon...

    Π’ ΠΊΠΎΠΌΠ°Π½Π΄Ρƒ DataDiscovery ΡˆΡƒΠΊΠ°Ρ”ΠΌΠΎ Π½Π° Ρ€ΠΎΠ·ΡˆΠΈΡ€Π΅Π½Π½Ρ Senior Data Scientist. 

     

    Наш Ρ–Π΄Π΅Π°Π»ΡŒΠ½ΠΈΠΉ ΠΊΠ°Π½Π΄ΠΈΠ΄Π°Ρ‚ ΠΌΠ°Ρ”:

    - 5+ Ρ€ΠΎΠΊΠΈ ΠΊΠΎΠΌΠ΅Ρ€Ρ†Ρ–ΠΉΠ½ΠΎΠ³ΠΎ досвіду Ρ€ΠΎΠ·Ρ€ΠΎΠ±ΠΊΠΈ.

     

    Навички:

    - Python Ρ‚Π° Π±Ρ–Π±Π»Ρ–ΠΎΡ‚Π΅ΠΊΠΈ машинного навчання: TensorFlow, PyTorch;

    - Π’Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³Ρ–Ρ— Big Data: Kafka, Amazon S3, Spark;

    - SQL Ρ‚Π° Π°Π½Π°Π»Ρ–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₯ΠΌΠ°Ρ€Π½Ρ– ΠΏΠ»Π°Ρ‚Ρ„ΠΎΡ€ΠΌΠΈ: AWS, GCP;

    ΠœΠ°Ρ‚Π΅ΠΌΠ°Ρ‚ΠΈΡ‡Π½Π° статистика: рСгрСсія, Ρ€ΠΎΠ·ΠΏΠΎΠ΄Ρ–Π» ймовірностСй, - ΠΏΠ΅Ρ€Π΅Π²Ρ–Ρ€ΠΊΠ° статистичних Π³Ρ–ΠΏΠΎΡ‚Π΅Π· Ρ‚ΠΎΡ‰ΠΎ;

    - ΠŸΡ–Π΄Ρ…ΠΎΠ΄ΠΈ машинного навчання: рСгрСсії, кластСризація, Π΄Π΅Ρ€Π΅Π²Π° Ρ€Ρ–ΡˆΠ΅Π½ΡŒ Ρ‚Π° Ρ–Π½ΡˆΡ–;

    - Алгоритми Π³Π»ΠΈΠ±ΠΎΠΊΠΎΠ³ΠΎ навчання: transformers, reinforcement learning, autoencoders, diffusion models, Ρ‚ΠΎΡ‰ΠΎ;

    - Досвід Ρ€ΠΎΠ·Ρ€ΠΎΠ±ΠΊΠΈ ΠΏΡ€ΠΎΠ΄ΡƒΠΊΡ‚Ρ–Π² AI: NLP, CV, Recsys, Generative AI;

    - MLOps.

     

    Π©ΠΎ ΠΏΠΎΡ‚Ρ€Ρ–Π±Π½ΠΎ Ρ€ΠΎΠ±ΠΈΡ‚ΠΈ:

    - Π’ΠΈΡ€Ρ–ΡˆΡƒΠ²Π°Ρ‚ΠΈ ΠΏΡ€ΠΎΠ΄ΡƒΠΊΡ‚ΠΎΠ²Ρ– Ρ‚Π° Π΄ΠΎΡΠ»Ρ–Π΄Π½ΠΈΡ†ΡŒΠΊΡ– Π²ΠΈΠΊΠ»ΠΈΠΊΠΈ ΠΊΡ€ΡƒΡ‚ΠΎΠ³ΠΎ ΡƒΠΊΡ€Π°Ρ—Π½ΡΡŒΠΊΠΎΠ³ΠΎ ΠΏΡ€ΠΎΠ΄ΡƒΠΊΡ‚Ρƒ;

    - ΠŸΡ€Π°Ρ†ΡŽΠ²Π°Ρ‚ΠΈ Π· Ρ€Π΅Π°Π»ΡŒΠ½ΠΈΠΌΠΈ Π΄Π°Π½ΠΈΠΌΠΈ Ρ€Π΅Π°Π»ΡŒΠ½ΠΈΡ… користувачів;

    - Π’ΠΈΠ²Ρ‡Π°Ρ‚ΠΈ Ρ‚Π° Π²ΠΏΡ€ΠΎΠ²Π°Π΄ΠΆΡƒΠ²Π°Ρ‚ΠΈ складні state-of-the-art Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠΈ Π² області машинного навчання для Π²ΠΈΡ€Ρ–ΡˆΠ΅Π½Π½Ρ ΠΏΡ€Π°ΠΊΡ‚ΠΈΡ‡Π½ΠΈΡ… Π·Π°Π΄Π°Ρ‡;

    - ΠžΡ†Ρ–Π½ΡŽΠ²Π°Ρ‚ΠΈ Ρ‚Π΅Ρ…Π½Ρ–Ρ‡Π½Ρ– компроміси ΠΏΠΎ ΠΊΠΎΠΆΠ½ΠΎΠΌΡƒ Ρ€Ρ–ΡˆΠ΅Π½Π½ΡŽ;

    - ΠŸΡ€Π°Ρ†ΡŽΠ²Π°Ρ‚ΠΈ Π² тісному співробітництві Π· Ρ–Π½ΡˆΠΈΠΌΠΈ ΠΊΠΎΠΌΠ°Π½Π΄Π°ΠΌΠΈ для дослідТСння Π½ΠΎΠ²ΠΈΡ… моТливостСй використання інструмСнтів AI.

     

    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.

     

    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· 138 views Β· 1 application Β· 26d

    Data Scientist

    Ukraine Β· Product Β· 1 year of experience Β· Pre-Intermediate
    Π’ ΠΊΠΎΠΌΠ°Π½Π΄Ρ– 10 Π΄Π°Ρ‚Π° саєнтистів. ΠŸΡ€Π°Ρ†ΡŽΡŽΡ‚ΡŒ Π· модСлями ΠΊΡ€Π΅Π΄ΠΈΡ‚Π½ΠΎΠ³ΠΎ скорингу, ΠΎΡ†Ρ–Π½ΠΊΠΈ Ρ€ΠΈΠ·ΠΈΠΊΡƒ ліквідності, ΠΊΠΎΠ»Π΅ΠΊΡˆΠ½Ρƒ, Π°Π½Ρ‚ΠΈΡ„Ρ€ΠΎΠ΄Ρƒ, ΠΌΠΎΠ½Ρ–Ρ‚ΠΎΡ€ΠΈΠ½Π³Ρƒ. ΠžΡΠ½ΠΎΠ²Π½Ρ– Π²ΠΈΠΌΠΎΠ³ΠΈ ΠžΠ‘ΠžΠ’'Π―Π—ΠšΠžΠ’Πž 1+ Ρ€Ρ–ΠΊ ΠΊΠΎΠΌΠ΅Ρ€Ρ†Ρ–ΠΉΠ½ΠΎΠ³ΠΎ досвіду Π½Π° Π°Π½Π°Π»ΠΎΠ³Ρ–Ρ‡Π½Ρ–ΠΉ посаді Π—Π°ΠΊΡ–Π½Ρ‡Π΅Π½Π° Π²ΠΈΡ‰Π° освіта (Ρ„Ρ–Π·ΠΈΠΊΠΎ-ΠΌΠ°Ρ‚Π΅ΠΌΠ°Ρ‚ΠΈΡ‡Π½Π°,...

    Π’ ΠΊΠΎΠΌΠ°Π½Π΄Ρ– 10 Π΄Π°Ρ‚Π° саєнтистів. ΠŸΡ€Π°Ρ†ΡŽΡŽΡ‚ΡŒ Π· модСлями ΠΊΡ€Π΅Π΄ΠΈΡ‚Π½ΠΎΠ³ΠΎ скорингу, ΠΎΡ†Ρ–Π½ΠΊΠΈ Ρ€ΠΈΠ·ΠΈΠΊΡƒ ліквідності, ΠΊΠΎΠ»Π΅ΠΊΡˆΠ½Ρƒ, Π°Π½Ρ‚ΠΈΡ„Ρ€ΠΎΠ΄Ρƒ, ΠΌΠΎΠ½Ρ–Ρ‚ΠΎΡ€ΠΈΠ½Π³Ρƒ.

     

    ΠžΡΠ½ΠΎΠ²Π½Ρ– Π²ΠΈΠΌΠΎΠ³ΠΈ

    • ΠžΠ‘ΠžΠ’'Π―Π—ΠšΠžΠ’Πž 1+ Ρ€Ρ–ΠΊ ΠΊΠΎΠΌΠ΅Ρ€Ρ†Ρ–ΠΉΠ½ΠΎΠ³ΠΎ досвіду Π½Π° Π°Π½Π°Π»ΠΎΠ³Ρ–Ρ‡Π½Ρ–ΠΉ посаді
    • Π—Π°ΠΊΡ–Π½Ρ‡Π΅Π½Π° Π²ΠΈΡ‰Π° освіта (Ρ„Ρ–Π·ΠΈΠΊΠΎ-ΠΌΠ°Ρ‚Π΅ΠΌΠ°Ρ‚ΠΈΡ‡Π½Π°, статистика, ΠΊΠΎΠΌΠΏ'ΡŽΡ‚Π΅Ρ€Π½Ρ– Π½Π°ΡƒΠΊΠΈ)
    • Π‘ΠΊΡ€ΡƒΠΏΡƒΠ»ΡŒΠΎΠ·Π½Ρ–ΡΡ‚ΡŒ, ΡƒΠ²Π°ΠΆΠ½Ρ–ΡΡ‚ΡŒ Ρ– Π²Ρ–Π΄ΠΏΠΎΠ²Ρ–Π΄Π°Π»ΡŒΠ½Ρ–ΡΡ‚ΡŒ
    • Досвід Ρ€ΠΎΠ·Ρ€ΠΎΠ±ΠΊΠΈ, впровадТСння Ρ‚Π° супроводТСння ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ
    • Досвід написання класів, ΠΏΠ°ΠΉΠΏΠ»Π°ΠΉΠ½Ρ–Π²
    • Знання Python
    • Π“Π°Ρ€Π½Π΅ знання SQL (Π°Π½Π°Π»Ρ–Π·ΡƒΡ”ΠΌΠΎ Π½Π°ΠΉΠ±Ρ–Π»ΡŒΡˆΡ– Π· усіх Π±Π°Π½ΠΊΡ–Π² Π±Π°Π·ΠΈ Π΄Π°Π½ΠΈΡ…)
    • Знання основних Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΡ–Π² ML (класичний ML, рСгрСсія, класифікація, ΠΏΡ€ΠΎΠ³Π½ΠΎΠ· часових рядів)

     

    Π‘ΡƒΠ΄Π΅ плюсом

    • Досвід Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Ρƒ Ρ„Ρ–Π½Ρ‚Π΅Ρ… Π΄ΠΎΠΌΠ΅Π½Ρ–
    • Досвід Π· Amazon Sagemaker, Amazon S3
    • Досвід Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Π· Git

     

    ΠžΡΠ½ΠΎΠ²Π½Ρ– обов’язки

    • Аналіз Ρ‚Π° валідація Π΄Π°Π½ΠΈΡ…
    • Π ΠΎΠ·Ρ€ΠΎΠ±ΠΊΠ° Ρ‚Π° впровадТСння ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΎΡ†Ρ–Π½ΠΊΠΈ Ρ€ΠΈΠ·ΠΈΠΊΡ–Π², які Π²Ρ–Π΄ΠΏΠΎΠ²Ρ–Π΄Π°ΡŽΡ‚ΡŒ ΠΊΡ€Π°Ρ‰ΠΈΠΌ світовим ΠΏΡ€Π°ΠΊΡ‚ΠΈΠΊΠ°ΠΌ
    • ΠœΠΎΠ½Ρ–Ρ‚ΠΎΡ€ΠΈΠ½Π³ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ, забСзпСчСння Π²Ρ–Π΄ΠΏΠΎΠ²Ρ–Π΄Π½ΠΎΡ— якості

     

    Π‘Π²ΠΎΡ—ΠΌ співробітникам ΠΌΠΈ ΠΏΡ€ΠΎΠΏΠΎΠ½ΡƒΡ”ΠΌΠΎ

    • Π ΠΎΠ±ΠΎΡ‚Ρƒ Π² Π½Π°ΠΉΠ±Ρ–Π»ΡŒΡˆΠΎΠΌΡƒ Ρ‚Π° Ρ–Π½Π½ΠΎΠ²Π°Ρ†Ρ–ΠΉΠ½ΠΎΠΌΡƒ Π±Π°Π½ΠΊΡƒ Π£ΠΊΡ€Π°Ρ—Π½ΠΈ
    • ΠžΡ„Ρ–Ρ†Ρ–ΠΉΠ½Π΅ ΠΏΡ€Π°Ρ†Π΅Π²Π»Π°ΡˆΡ‚ΡƒΠ²Π°Π½Π½Ρ Ρ‚Π° 24 ΠΊΠ°Π»Π΅Π½Π΄Π°Ρ€Π½ΠΈΡ… Π΄Π½Ρ– відпустки
    • ΠšΠΎΠΌΠΏΠ΅Π½ΡΠ°Ρ†Ρ–ΡŽ лікарняних
    • ΠšΠΎΠ½ΠΊΡƒΡ€Π΅Π½Ρ‚Π½Ρƒ Π·Π°Ρ€ΠΎΠ±Ρ–Ρ‚Π½Ρƒ ΠΏΠ»Π°Ρ‚Ρƒ
    • Бонуси, прСмія Π²Ρ–Π΄ΠΏΠΎΠ²Ρ–Π΄Π½ΠΎ Π΄ΠΎ ΠΏΠΎΠ»Ρ–Ρ‚ΠΈΠΊΠΈ ΠΊΠΎΠΌΠΏΠ°Π½Ρ–Ρ—
    • ΠœΠ΅Π΄ΠΈΡ‡Π½Π΅ страхування 
    • ΠšΠΎΡ€ΠΏΠΎΡ€Π°Ρ‚ΠΈΠ²Π½Π΅ навчання
    • ΠœΠΎΠΆΠ»ΠΈΠ²Ρ–ΡΡ‚ΡŒ Π²Ρ–Π΄Π΄Π°Π»Π΅Π½ΠΎΠ³ΠΎ Ρ„ΠΎΡ€ΠΌΠ°Ρ‚Ρƒ Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ
    • ΠšΠΎΡ€ΠΏΠΎΡ€Π°Ρ‚ΠΈΠ²Π½Ρƒ фінансову Π΄ΠΎΠΏΠΎΠΌΠΎΠ³Ρƒ Ρƒ ΠΊΡ€ΠΈΡ‚ΠΈΡ‡Π½ΠΈΡ… ситуаціях
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  • Β· 145 views Β· 9 applications Β· 29d

    Junior / Middle Data Scientist

    Ukraine Β· Product Β· 1 year of experience Ukrainian Product πŸ‡ΊπŸ‡¦
    SKELAR β€” ΡƒΠΊΡ€Π°Ρ—Π½ΡΡŒΠΊΠΈΠΉ venture builder, який Π±ΡƒΠ΄ΡƒΡ” ΠΌΡ–ΠΆΠ½Π°Ρ€ΠΎΠ΄Π½Ρ– tech-бізнСси. Π Π°Π·ΠΎΠΌ Ρ–Π· ΠΊΠΎ-Ρ„Π°ΡƒΠ½Π΄Π΅Ρ€Π°ΠΌΠΈ Π·Π±ΠΈΡ€Π°Ρ”ΠΌΠΎ ΡΠΈΠ»ΡŒΠ½Ρ– ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ, Ρ‰ΠΎΠ± ΠΏΠ΅Ρ€Π΅ΠΌΠ°Π³Π°Ρ‚ΠΈ Π½Π° Π³Π»ΠΎΠ±Π°Π»ΡŒΠ½ΠΈΡ… Ρ€ΠΈΠ½ΠΊΠ°Ρ…. Π‘ΡŒΠΎΠ³ΠΎΠ΄Π½Ρ– Π² SKELAR β€” дСсяток бізнСсів Ρƒ Ρ€Ρ–Π·Π½ΠΈΡ… Π½Ρ–ΡˆΠ°Ρ… Π²Ρ–Π΄ EdTech Π΄ΠΎ SaaS. Π¦Π΅ ΠΊΠΎΠΌΠΏΠ°Π½Ρ–Ρ—, Ρ‰ΠΎ ΠΌΠ°ΡŽΡ‚ΡŒ...

    SKELAR β€” ΡƒΠΊΡ€Π°Ρ—Π½ΡΡŒΠΊΠΈΠΉ venture builder, який Π±ΡƒΠ΄ΡƒΡ” ΠΌΡ–ΠΆΠ½Π°Ρ€ΠΎΠ΄Π½Ρ– tech-бізнСси. Π Π°Π·ΠΎΠΌ Ρ–Π· ΠΊΠΎ-Ρ„Π°ΡƒΠ½Π΄Π΅Ρ€Π°ΠΌΠΈ Π·Π±ΠΈΡ€Π°Ρ”ΠΌΠΎ ΡΠΈΠ»ΡŒΠ½Ρ– ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ, Ρ‰ΠΎΠ± ΠΏΠ΅Ρ€Π΅ΠΌΠ°Π³Π°Ρ‚ΠΈ Π½Π° Π³Π»ΠΎΠ±Π°Π»ΡŒΠ½ΠΈΡ… Ρ€ΠΈΠ½ΠΊΠ°Ρ….
     

    Π‘ΡŒΠΎΠ³ΠΎΠ΄Π½Ρ– Π² SKELAR β€” дСсяток бізнСсів Ρƒ Ρ€Ρ–Π·Π½ΠΈΡ… Π½Ρ–ΡˆΠ°Ρ… Π²Ρ–Π΄ EdTech Π΄ΠΎ SaaS. Π¦Π΅ ΠΊΠΎΠΌΠΏΠ°Π½Ρ–Ρ—, Ρ‰ΠΎ ΠΌΠ°ΡŽΡ‚ΡŒ Π²Ρ–Π΄Π·Π½Π°ΠΊΠΈ Π²Ρ–Π΄ Product Hunt, ΠΏΠΎΡ‚Ρ€Π°ΠΏΠ»ΡΡŽΡ‚ΡŒ Ρƒ Ρ€Π΅ΠΉΡ‚ΠΈΠ½Π³ΠΈ ВОП-стартапів Ρ‚Π° ΠΏΡ€ΠΎΠ΄ΡƒΠΊΡ‚ΠΎΠ²ΠΈΡ… ΠΊΠΎΠΌΠΏΠ°Π½Ρ–ΠΉ Π£ΠΊΡ€Π°Ρ—Π½ΠΈ, Π·Π°ΠΉΠΌΠ°ΡŽΡ‚ΡŒ Π½Π°ΠΉΠ²ΠΈΡ‰Ρ– Ρ‰Π°Π±Π»Ρ– Π² AppStore Ρ‚Π° Ρ€ΠΎΠ·Ρ€ΠΎΠ±Π»ΡΡŽΡ‚ΡŒ ΠΏΠ»Π°Ρ‚Ρ„ΠΎΡ€ΠΌΠΈ, якими ΠΊΠΎΡ€ΠΈΡΡ‚ΡƒΡŽΡ‚ΡŒΡΡ ΠΌΡ–Π»ΡŒΠΉΠΎΠ½ΠΈ людСй. А Ρ‰Π΅ ΠΏΡ€ΠΎ бізнСси SKELAR ΠΏΠΈΡˆΡƒΡ‚ΡŒ TechCrunch, Wired Ρ‚Π° Ρ–Π½ΡˆΡ– світові ΠΌΠ΅Π΄Ρ–Π°.
     

    ΠŸΠΈΡˆΠ°Ρ”ΠΌΠΎΡΡ сильною командою Ρ–Π· 800+ Ρ„Π°Ρ…Ρ–Π²Ρ†Ρ–Π², які ΠΌΠ°ΡŽΡ‚ΡŒ ΠΊΡ€ΡƒΡ‚Ρƒ СкспСртизу ΠΉ Π°ΠΌΠ±Ρ–Ρ‚Π½Ρ– Ρ†Ρ–Π»Ρ–. ΠΠ°ΡˆΡ– люди β€” Π½Π°ΠΉΡ†Ρ–Π½Π½Ρ–ΡˆΠΈΠΉ Π°ΠΊΡ‚ΠΈΠ² ΠΊΠΎΠΌΠΏΠ°Π½Ρ–Ρ—, Ρ‚ΠΎΠΆ ΠΌΠΈ ΠΎΠ±ΠΈΡ€Π°Ρ”ΠΌΠΎ Π±ΡƒΠ΄ΡƒΠ²Π°Ρ‚ΠΈ бізнСси Ρ€Π°Π·ΠΎΠΌ Π· Π½Π°ΠΉΠΊΡ€Π°Ρ‰ΠΈΠΌΠΈ Ρ‚Π°Π»Π°Π½Ρ‚Π°ΠΌΠΈ Π½Π° Ρ€ΠΈΠ½ΠΊΡƒ.
     

    Π—Π°Ρ€Π°Π· ΠΌΠΈ Ρƒ ΠΏΠΎΡˆΡƒΠΊΡƒ Data Scientist Ρƒ Π½Π°ΡˆΡƒ ΠΏΠΎΡ€Ρ‚Ρ„Π΅Π»ΡŒΠ½Ρƒ ΠΊΠΎΠΌΠΏΠ°Π½Ρ–ΡŽ TENTENS Tech.
     

    TENTENS Tech β€” ΡƒΠΊΡ€Π°Ρ—Π½ΡΡŒΠΊΠ° IT-компанія, Ρ‰ΠΎ розробляє ΠΏΠ»Π°Ρ‚Ρ„ΠΎΡ€ΠΌΠΈ Ρƒ сфСрі стрімінгу Ρ‚Π° social discovery. Команда TENTENS Tech ΠΌΠ°Ρ” досвід ΡƒΡΠΏΡ–ΡˆΠ½ΠΈΡ… запусків дСсятків ΠΏΠ»Π°Ρ‚Ρ„ΠΎΡ€ΠΌ, якими ΠΊΠΎΡ€ΠΈΡΡ‚ΡƒΡŽΡ‚ΡŒΡΡ ΠΌΡ–Π»ΡŒΠΉΠΎΠ½ΠΈ людСй Π½Π° всіх ΠΊΠΎΠ½Ρ‚ΠΈΠ½Π΅Π½Ρ‚Π°Ρ… світу (ΠΎΠΊΡ€Ρ–ΠΌ Антарктиди, ΠΏΠΎΠΊΠΈ Ρ‰ΠΎ). А слоган We don’t think limits Π²Ρ–Π΄ΠΎΠ±Ρ€Π°ΠΆΠ°Ρ” як стратСгічнС мислСння ΠΊΠΎΠΌΠΏΠ°Π½Ρ–Ρ—, Ρ‚Π°ΠΊ Ρ– ΠΌΠΎΡ‚ΠΈΠ²Π°Ρ†Ρ–ΡŽ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ Π·Π°Π²ΠΆΠ΄ΠΈ ΠΌΡ‡Π°Ρ‚ΠΈ Π΄Π°Π»Π΅ΠΊΠΎ Π·Π° Π³ΠΎΡ€ΠΈΠ·ΠΎΠ½Ρ‚. ΠœΠ°Ρ”ΠΌΠΎ ΠΏΠΎΡ‚ΡƒΠΆΠ½Ρƒ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ Π°Π½Π°Π»Ρ–Ρ‚ΠΈΠΊΠΈ Π· 20+ співробітників.
     

    Π¨ΡƒΠΊΠ°Ρ”ΠΌΠΎ: Ρ‚Π°Π»Π°Π½ΠΎΠ²ΠΈΡ‚ΠΎΠ³ΠΎ data scientist-Π° Π· досвідом Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Ρ€Ρ–ΠΊ+, який full-time Π±ΡƒΠ΄Π΅ Ρ€Π°Π·ΠΎΠΌ Π· ΠΊΠΎΠ»Π΅Π³Π°ΠΌΠΈ розробляти Π΅Ρ„Π΅ΠΊΡ‚ΠΈΠ²Π½Ρ– ΠΌΠΎΠ΄Π΅Π»Ρ– для ΠΏΠΎΡ‚Ρ€Π΅Π± бізнСсу Ρ– Ρ€ΠΎΠ·Π²ΠΈΠ²Π°Ρ‚ΠΈ Π²ΠΆΠ΅ наявні. Π£ вас Π±ΡƒΠ΄Π΅ ΠΌΠΎΠΆΠ»ΠΈΠ²Ρ–ΡΡ‚ΡŒ ΠΏΡ€Π°Ρ†ΡŽΠ²Π°Ρ‚ΠΈ Ρ–Π· Ρ€Ρ–Π·Π½ΠΎΠΌΠ°Π½Ρ–Ρ‚Π½ΠΈΠΌΠΈ Ρ‚ΠΈΠΏΠ°ΠΌΠΈ Π΄Π°Π½ΠΈΡ… Ρ‚Π° модСлями, застосовувати Π½ΠΎΠ²Ρ–Ρ‚Π½Ρ– ΠΏΡ–Π΄Ρ…ΠΎΠ΄ΠΈ Π² області AΠ† Ρ‚Π° ΠΏΡ€ΠΎΠΏΠΎΠ½ΡƒΠ²Π°Ρ‚ΠΈ Π½Π°ΠΉΠΊΡ€Π°Ρ‰Ρ– Ρ€Ρ–ΡˆΠ΅Π½Π½Ρ для ΠΏΠΎΡ‚Ρ€Π΅Π± бізнСсу.
     

    Π―ΠΊΡ– Π²ΠΈΠΊΠ»ΠΈΠΊΠΈ Ρ‡Π΅ΠΊΠ°ΡŽΡ‚ΡŒ Π½Π° Ρ‚Π΅Π±Π΅ Π² Ρ€ΠΎΠ»Ρ– Data Scientist:

    β€” Π ΠΎΠ·Π²ΠΈΡ‚ΠΎΠΊ Π²ΠΆΠ΅ наявних ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Ρ– Ρ—Ρ… сСрвісів (Π°Π½Ρ‚ΠΈΡ„Ρ€ΠΎΠ΄, ΠΎΡ†Ρ–Π½ΠΊΠ° ΠΌΠ°Ρ€ΠΊΠ΅Ρ‚ΠΈΠ½Π³Ρƒ, модСрація);
    β€” Бпівпраця Π· Π°Π½Π°Π»Ρ–Ρ‚ΠΈΠΊΠ°ΠΌΠΈ, DE-спСціалістами Ρ‚Π° Ρ–Π½ΡˆΠΈΠΌΠΈ Ρ–Π½ΠΆΠ΅Π½Π΅Ρ€Π°ΠΌΠΈ для ΠΏΠΎΠ±ΡƒΠ΄ΠΎΠ²ΠΈ складних ML-ΠΏΠ°ΠΉΠΏΠ»Π°ΠΉΠ½Ρ–Π²;
    β€” End-to-end Ρ€ΠΎΠ·Ρ€ΠΎΠ±ΠΊΠ° Ρ– впровадТСння Π½ΠΎΠ²ΠΈΡ… ML-сСрвісів;
    β€” ЗабСзпСчСння якості ΠΏΠ°ΠΉΠΏΠ»Π°ΠΉΠ½Ρ–Π² трСнування Ρ‚Π° тСстування ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ;
    β€” Π ΠΎΠ·Ρ€ΠΎΠ±ΠΊΠ° Ρ– впровадТСння систСм ΠΌΠΎΠ½Ρ–Ρ‚ΠΎΡ€ΠΈΠ½Π³Ρƒ Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ;
     

    Що для нас ваТливо:

    β€” Π’ΠΏΠ΅Π²Π½Π΅Π½Π΅ володіння SQL Ρ‚Π° Python;
    β€” Π’ΠΏΠ΅Π²Π½Π΅Π½Ρ– знання ΠΌΠ°Ρ‚Π΅ΠΌΠ°Ρ‚ΠΈΠΊΠΈ, Ρ‚Π΅ΠΎΡ€Ρ–Ρ— ймовірностСй Ρ‚Π° статистики;
    β€” Знання класичних ML-Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΡ–Π²;
    β€” Досвід Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Π· ML-Ρ„Ρ€Π΅ΠΉΠΌΠ²ΠΎΡ€ΠΊΠ°ΠΌΠΈ Ρ‚Π° Π±Ρ–Π±Π»Ρ–ΠΎΡ‚Π΅ΠΊΠ°ΠΌΠΈ для ΠΎΠ±Ρ€ΠΎΠ±ΠΊΠΈ Π΄Π°Π½ΠΈΡ…;
    β€” Досвід Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Π· GCP/Azure/AWS;
    β€” Досвід Ρ€Π΅Π°Π»Ρ–Π·Π°Ρ†Ρ–Ρ— Ρ– ΠΏΡ–Π΄Ρ‚Ρ€ΠΈΠΌΠΊΠΈ ΠΏΠ°ΠΉΠΏΠ»Π°ΠΉΠ½Ρ–Π² трСнування/тСстування ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ;
    β€” Знання Docker, розуміння IaS;
    β€” ΠΠΊΡƒΡ€Π°Ρ‚Π½Ρ–ΡΡ‚ΡŒ, ΡƒΠ²Π°Π³Π° Π΄ΠΎ Π΄Π΅Ρ‚Π°Π»Π΅ΠΉ, ΠΊΡ€ΠΈΡ‚ΠΈΡ‡Π½Π΅ мислСння;
    β€” Вміння ΠΏΡ€Π°Ρ†ΡŽΠ²Π°Ρ‚ΠΈ Π² ΠΊΠΎΠΌΠ°Π½Π΄Ρ–.
     

    SKELAR foundation β€” Π±Π»Π°Π³ΠΎΠ΄Ρ–ΠΉΠ½ΠΈΠΉ Ρ„ΠΎΠ½Π΄, створСний співробітниками ΠΊΠΎΠΌΠΏΠ°Π½Ρ–Ρ—. Π’ ΠΌΠ΅ΠΆΠ°Ρ… Ρ–Π½Ρ–Ρ†Ρ–Π°Ρ‚ΠΈΠ²ΠΈ ΡΡ‚Π²ΠΎΡ€ΡŽΡ”ΠΌΠΎ Ρ‚Π° фінансуємо ΠΏΡ€ΠΎΡ”ΠΊΡ‚ΠΈ, Ρ‰ΠΎ ΡΠΏΡ€ΠΈΡΡŽΡ‚ΡŒ подоланню наслідків Π²Ρ–ΠΉΠ½ΠΈ Ρ‚Π° Π²Ρ–Π΄Π½ΠΎΠ²Π»Π΅Π½Π½ΡŽ Π£ΠΊΡ€Π°Ρ—Π½ΠΈ.

    SKELAR β€” сСрСдовищС для саморСалізації людСй, які Π·Π΄Π°Ρ‚Π½Ρ– створити ΡƒΡΠΏΡ–ΡˆΠ½Ρ– ΠΊΠΎΠΌΠΏΠ°Π½Ρ–Ρ—. Ми Ρ‚Π°ΠΊΡ– ΠΊΠΎΠΌΠΏΠ°Π½Ρ–Ρ— Π½Π°Π·ΠΈΠ²Π°Ρ”ΠΌΠΎ the next big everything. Π’Ρ–Ρ€ΠΈΠΌΠΎ Π² Ρ—Ρ… ΠΏΠΎΡ‚ΡƒΠΆΠ½Ρ–ΡΡ‚ΡŒ Ρ‚Π° ΠΌΠ°ΡΡˆΡ‚Π°Π±.

    Ми ΠΏΠ»Π°Π½ΡƒΡ”ΠΌΠΎ ΠΉ Π½Π°Π΄Π°Π»Ρ– Ρ€ΠΎΠ·Π²ΠΈΠ²Π°Ρ‚ΠΈ tech-бізнСси, ΠΏΡ–Π΄ΠΊΠΎΡ€ΡŽΠ²Π°Ρ‚ΠΈ Π³Π»ΠΎΠ±Π°Π»ΡŒΠ½Ρ– Ρ€ΠΈΠ½ΠΊΠΈ Ρ‚Π° ΠΏΡ€Π°Ρ†ΡŽΠ²Π°Ρ‚ΠΈ задля ΠΏΠ΅Ρ€Π΅ΠΌΠΎΠ³ΠΈ Π£ΠΊΡ€Π°Ρ—Π½ΠΈ πŸ‡ΊπŸ‡¦
     

    Для Ρ†ΡŒΠΎΠ³ΠΎ створили всі моТливості всСрСдині нашого Π²Π΅Π½Ρ‡ΡƒΡ€ Π±Ρ–Π»Π΄Π΅Ρ€Π°:
    β€” 8 інфраструктурних ΠΊΠΎΠΌΠ°Π½Π΄, які Π΄ΠΎΠΏΠΎΠΌΠ°Π³Π°ΡŽΡ‚ΡŒ бізнСсам Π·Π°ΠΊΡ€ΠΈΠ²Π°Ρ‚ΠΈ Π±ΡƒΠ΄ΡŒ-які питання: Π²Ρ–Π΄ Ρ€Π΅ΠΊΡ€ΡƒΡ‚ΠΈΠ½Π³Ρƒ Ρ– ΠΊΠΎΠΌΡƒΠ½Ρ–ΠΊΠ°Ρ†Ρ–ΠΉ Π΄ΠΎ фінансів Ρ‚Π° ΡŽΡ€ΠΈΠ΄ΠΈΡ‡Π½ΠΈΡ… ΠΏΠΈΡ‚Π°Π½ΡŒ;
    β€” Π‘ΠΏΡ–Π»ΡŒΠ½ΠΎΡ‚Π° Ρ„Π°ΡƒΠ½Π΄Π΅Ρ€Ρ–Π², які Π²ΠΆΠ΅ запустили Π½Π΅ ΠΎΠ΄ΠΈΠ½ бізнСс ΠΉ ΠΌΠΎΠΆΡƒΡ‚ΡŒ ділитися ΠΏΡ€Π°ΠΊΡ‚ΠΈΡ‡Π½ΠΈΠΌ досвідом;
    β€” Π’Π½ΡƒΡ‚Ρ€Ρ–ΡˆΠ½Ρ– ΠΊΠ»ΡƒΠ±ΠΈ Π·Π° профСсійними напрямками: ΠΌΠ°Ρ€ΠΊΠ΅Ρ‚ΠΈΠ½Π³, Ρ€ΠΎΠ·Ρ€ΠΎΠ±ΠΊΠ°, фінанси, Ρ€Π΅ΠΊΡ€ΡƒΡ‚ΠΈΠ½Π³;
    β€” Π’Ρ€Π΅Π½Ρ–Π½Π³ΠΈ, курси, відвідування ΠΊΠΎΠ½Ρ„Π΅Ρ€Π΅Π½Ρ†Ρ–ΠΉ;
    β€” ΠœΠ΅Π΄ΠΈΡ‡Π½Π΅ страхування, ΠΊΠΎΡ€ΠΏΠΎΡ€Π°Ρ‚ΠΈΠ²Π½ΠΈΠΉ Π»Ρ–ΠΊΠ°Ρ€.

    Π”Π°Π²Π°ΠΉ Ρ€Π°Π·ΠΎΠΌ Π±ΡƒΠ΄ΡƒΠ²Π°Ρ‚ΠΈ the next big everything!

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    Ми ΡˆΡƒΠΊΠ°Ρ”ΠΌΠΎ Ρ‚Π°Π»Π°Π½ΠΎΠ²ΠΈΡ‚ΠΎΠ³ΠΎ Intern Data Scientist, який Π·Π°Ρ…ΠΎΠΏΠ»ΡŽΡ”Ρ‚ΡŒΡΡ Π°Π½Π°Π»Ρ–Π·ΠΎΠΌ Π΄Π°Π½ΠΈΡ…, ΠΏΡ€Π°Π³Π½Π΅ Ρ€ΠΎΠ·Π²ΠΈΠ²Π°Ρ‚ΠΈ ΠΏΡ€Π°ΠΊΡ‚ΠΈΡ‡Π½Ρ– Π½Π°Π²ΠΈΡ‡ΠΊΠΈ Π² ΠΏΠΎΠ±ΡƒΠ΄ΠΎΠ²Ρ– ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ, Ρ€ΠΎΠ±ΠΎΡ‚Ρ– Π· Π²Π΅Π»ΠΈΠΊΠΈΠΌΠΈ масивами Ρ–Π½Ρ„ΠΎΡ€ΠΌΠ°Ρ†Ρ–Ρ— Ρ‚Π° ΠΌΠ°Ρ” баТання навчатися ΠΉ зростати Ρ€Π°Π·ΠΎΠΌ Ρ–Π· командою. Π¦Π΅ Ρ‡ΡƒΠ΄ΠΎΠ²Π° ΠΌΠΎΠΆΠ»ΠΈΠ²Ρ–ΡΡ‚ΡŒ для...

    Ми ΡˆΡƒΠΊΠ°Ρ”ΠΌΠΎ Ρ‚Π°Π»Π°Π½ΠΎΠ²ΠΈΡ‚ΠΎΠ³ΠΎ Intern Data Scientist, який Π·Π°Ρ…ΠΎΠΏΠ»ΡŽΡ”Ρ‚ΡŒΡΡ Π°Π½Π°Π»Ρ–Π·ΠΎΠΌ Π΄Π°Π½ΠΈΡ…, ΠΏΡ€Π°Π³Π½Π΅ Ρ€ΠΎΠ·Π²ΠΈΠ²Π°Ρ‚ΠΈ ΠΏΡ€Π°ΠΊΡ‚ΠΈΡ‡Π½Ρ– Π½Π°Π²ΠΈΡ‡ΠΊΠΈ Π² ΠΏΠΎΠ±ΡƒΠ΄ΠΎΠ²Ρ– ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ, Ρ€ΠΎΠ±ΠΎΡ‚Ρ– Π· Π²Π΅Π»ΠΈΠΊΠΈΠΌΠΈ масивами Ρ–Π½Ρ„ΠΎΡ€ΠΌΠ°Ρ†Ρ–Ρ— Ρ‚Π° ΠΌΠ°Ρ” баТання навчатися ΠΉ зростати Ρ€Π°Π·ΠΎΠΌ Ρ–Π· командою. Π¦Π΅ Ρ‡ΡƒΠ΄ΠΎΠ²Π° ΠΌΠΎΠΆΠ»ΠΈΠ²Ρ–ΡΡ‚ΡŒ для старту кар’єри Ρƒ сфСрі Data Science!

     

    ΠžΡΠ½ΠΎΠ²Π½Ρ– обов’язки
    - Π—Π±Ρ–Ρ€, консолідація Ρ‚Π° ΠΏΡ–Π΄Π³ΠΎΡ‚ΠΎΠ²ΠΊΠ° Π΄Π°Π½ΠΈΡ… Π· Ρ€Ρ–Π·Π½ΠΈΡ… Π΄ΠΆΠ΅Ρ€Π΅Π».  
    - Π£Ρ‡Π°ΡΡ‚ΡŒ Ρƒ Ρ€ΠΎΠ·Ρ€ΠΎΠ±Ρ†Ρ– Ρ‚Π° ΠΏΠΎΠΊΡ€Π°Ρ‰Π΅Π½Π½Ρ– Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΡ–Π² Π°Π½Π°Π»Ρ–Π·Ρƒ Π΄Π°Π½ΠΈΡ….  
    - ΠŸΠΎΠ±ΡƒΠ΄ΠΎΠ²Π° Π±Π°Π·ΠΎΠ²ΠΈΡ… Π°Π½Π°Π»Ρ–Ρ‚ΠΈΡ‡Π½ΠΈΡ… Ρ‚Π° ΠΏΡ€ΠΎΠ³Π½ΠΎΠ·Π½ΠΈΡ… ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ.  
    - БтворСння Π·Π°ΠΏΠΈΡ‚Ρ–Π² Π΄ΠΎ Π±Π°Π· Π΄Π°Π½ΠΈΡ… Ρ– ΠΏΡ–Π΄Π³ΠΎΡ‚ΠΎΠ²ΠΊΠ° Π·Π²Ρ–Ρ‚Ρ–Π².  
    - Візуалізація Π΄Π°Π½ΠΈΡ… для Π²Π½ΡƒΡ‚Ρ€Ρ–ΡˆΠ½Ρ–Ρ… ΠΊΠΎΠΌΠ°Π½Π΄ Ρ‚Π° прийняття Ρ€Ρ–ΡˆΠ΅Π½ΡŒ.  
    - ВивчСння Ρ‚Π° застосування статистичних ΠΏΡ–Π΄Ρ…ΠΎΠ΄Ρ–Π² Π΄ΠΎ Π°Π½Π°Π»Ρ–Π·Ρƒ.  
    - Бпівпраця Π· Π°Π½Π°Π»Ρ–Ρ‚ΠΈΠΊΠ°ΠΌΠΈ, Ρ€ΠΎΠ·Ρ€ΠΎΠ±Π½ΠΈΠΊΠ°ΠΌΠΈ Ρ‚Π° бізнСс-ΠΊΠΎΠΌΠ°Π½Π΄Π°ΠΌΠΈ.  
    - Автоматизація ΠΏΠΎΠ²Ρ‚ΠΎΡ€ΡŽΠ²Π°Π½ΠΈΡ… Π°Π½Π°Π»Ρ–Ρ‚ΠΈΡ‡Π½ΠΈΡ… Π·Π°Π΄Π°Ρ‡.

     

    Π’ΠΈΠΌΠΎΠ³ΠΈ Π΄ΠΎ ΠΊΠ°Π½Π΄ΠΈΠ΄Π°Ρ‚Π°
    - ΠΠ°ΡΠ²Π½Ρ–ΡΡ‚ΡŒ Π·Π°ΠΊΡ–Π½Ρ‡Π΅Π½ΠΎΡ— Π²ΠΈΡ‰ΠΎΡ— освіти Π·Π° ΡΠΏΠ΅Ρ†Ρ–Π°Π»ΡŒΠ½Ρ–ΡΡ‚ΡŽ
    - Досвід навчання Π°Π±ΠΎ стаТування Ρƒ сфСрі Data Science / Π°Π½Π°Π»Ρ–Ρ‚ΠΈΠΊΠΈ Π΄Π°Π½ΠΈΡ….  
    - Π‘Π°Π·ΠΎΠ²Π΅ володіння Python (pandas, numpy, sklearn Ρ‚ΠΎΡ‰ΠΎ).  
    - Знання основ SQL Ρ‚Π° вміння ΠΏΡ€Π°Ρ†ΡŽΠ²Π°Ρ‚ΠΈ Π· Π±Π°Π·Π°ΠΌΠΈ Π΄Π°Π½ΠΈΡ….  
    - Розуміння Π±Π°Π·ΠΎΠ²ΠΈΡ… статистичних ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ–Π² Ρ‚Π° ΠΏΡ€ΠΈΠ½Ρ†ΠΈΠΏΡ–Π² модСлювання.  
    - Навички Π²Ρ–Π·ΡƒΠ°Π»Ρ–Π·Π°Ρ†Ρ–Ρ— Π΄Π°Π½ΠΈΡ… (Power BI, Tableau Π°Π±ΠΎ matplotlib/seaborn).  
    - БаТання навчатися ΠΉ Ρ€ΠΎΠ·Π²ΠΈΠ²Π°Ρ‚ΠΈ Π½Π°Π²ΠΈΡ‡ΠΊΠΈ Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ Π· Big Data Ρ‚Π° Ρ…ΠΌΠ°Ρ€Π½ΠΈΠΌΠΈ тСхнологіями (Azure β€” Π±ΡƒΠ΄Π΅ ΠΏΠ΅Ρ€Π΅Π²Π°Π³ΠΎΡŽ).  
    - АналітичнС мислСння, ΡƒΠ²Π°ΠΆΠ½Ρ–ΡΡ‚ΡŒ Π΄ΠΎ Π΄Π΅Ρ‚Π°Π»Π΅ΠΉ, Ρ–Π½Ρ–Ρ†Ρ–Π°Ρ‚ΠΈΠ²Π½Ρ–ΡΡ‚ΡŒ.

     

    Ми ΠΏΡ€ΠΎΠΏΠΎΠ½ΡƒΡ”ΠΌΠΎ
    - Π“Π½ΡƒΡ‡ΠΊΠΈΠΉ Π³Ρ€Π°Ρ„Ρ–ΠΊ Ρ‚Π° Π²Ρ–Π΄Π΄Π°Π»Π΅Π½ΠΈΠΉ Ρ„ΠΎΡ€ΠΌΠ°Ρ‚ Ρ€ΠΎΠ±ΠΎΡ‚ΠΈ.  
    - Π ΠΎΠ±ΠΎΡ‚Ρƒ Π½Π°Π΄ Ρ€Π΅Π°Π»ΡŒΠ½ΠΈΠΌΠΈ кСйсами ΠΉ Π°Π½Π°Π»Ρ–Ρ‚ΠΈΡ‡Π½ΠΈΠΌΠΈ Π·Π°Π΄Π°Ρ‡Π°ΠΌΠΈ.  
    - ΠœΠ΅Π½Ρ‚ΠΎΡ€ΡΡ‚Π²ΠΎ Π· Π±ΠΎΠΊΡƒ досвідчСних Data Scientist-Ρ–Π².  
    - ΠœΠΎΠΆΠ»ΠΈΠ²Ρ–ΡΡ‚ΡŒ подальшого ΠΏΡ€Π°Ρ†Π΅Π²Π»Π°ΡˆΡ‚ΡƒΠ²Π°Π½Π½Ρ Π·Π° Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Π°ΠΌΠΈ стаТування.  
    - Π”Ρ€ΡƒΠΆΠ½ΡŽ атмосфСру Ρ‚Π° ΠΏΡ–Π΄Ρ‚Ρ€ΠΈΠΌΠΊΡƒ Ρ€ΠΎΠ·Π²ΠΈΡ‚ΠΊΡƒ.

     

    Π―ΠΊΡ‰ΠΎ Ρ‚ΠΈ Ρ…ΠΎΡ‡Π΅Ρˆ Ρ€ΠΎΠ·ΠΏΠΎΡ‡Π°Ρ‚ΠΈ кар’єру Π² Data Science, ΠΏΡ€Π°Ρ†ΡŽΠ²Π°Ρ‚ΠΈ Π· Π΄Π°Π½ΠΈΠΌΠΈ, Ρ‰ΠΎ ΠΌΠ°ΡŽΡ‚ΡŒ значСння, Ρ– зростати профСсійно β€” надсилай своє Ρ€Π΅Π·ΡŽΠΌΠ΅!

     

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