Jobs Data Science

Position Overview

We are seeking an experienced Data Scientist/ML Engineer specializing in neural networks, with 3+ years experience in the applied field. The ideal candidate should be a great mentor and team player; python ninja with a strong background in various neural network architectures (recurrent, convolutional, feedforward, etc.) and a deep understanding of developing, tuning, and deploying different architectures. This role also requires excellent Python programming skills and a solid foundation in data analysis and statistics. If you strive in a fast pace environment, with tight deadlines but fast professional growth, you are welcome in our team!

Key Responsibilities:

• Create statistical summaries to support hypothesis testing and data-driven decisions during EDA
• Implement data preparation and feature engineering pipelines for the models
• Plan and implement algorithms for predictive modeling.
• Provide continuous improvement of models in production
• Lead the ML-driven python coding for end to end model deliveries, support our ML-related libraries/
• Collaborate with a cross-functional team of specialists, including senior and junior data scientists, Python developers and ML engineers, data analysts, and DevOps specialists.
• Provide expertise in tuning loss functions, metrics, sample weights adjustment, hyperparameter tuning and model improvement in general.
• Generate detailed evaluation reports, summarizing key findings and presenting actionable insights to stakeholders.
• Keep up with tight deadlines, agile environment of work with evolving objectives and KPIs, having the highest level of organisation and self management to provide a full work clarity, extensive tracking and documentation of your work.

Required Skills and Qualifications:

• Minimum of 3 years of professional experience as a Data Scientist or Machine Learning Engineer.
• Proficient in building custom neural networks using PyTorch.
• Strong experience with various neural network architectures specialised for time-series modelling and tabular data predictive modelling 
• Proficiency with neural network layers (like LSTM, GRU, Conv1D, Dense, Dropout, BatchNormalization) and activation functions (ReLU, Sigmoid, Tanh, Softmax).
• Experience with time series data, including loading, cleaning, and feature engineering using libraries like pandas, numpy. Knowledge of Darts library would be a large bonus.
• Expertise in model development, including selecting and developing models from the Darts library and building custom neural network architectures.
• In-depth knowledge of Python programming and relevant libraries (e.g., Scikit-learn, Pandas, PyTorch, Shap). We want to emphasize this requirement of excellency in python, including good working OOP knowledge. We do noе accept candidates with partial experience in python, as our projects require solid programming skills for writing and supporting data science related functionalities and libraries
• Solid understanding of statistics and data analysis.
• Skilled in using and tuning loss functions such as MSE, MAE, Cross-Entropy Loss, and custom loss functions relevant to time series forecasting.
• Experience with hyperparameter optimization using libraries like Optuna or Hyperopt.
• Capable of implementing and optimizing training loops in PyTorch, including data loaders and training validation steps.
• Knowledge of time series-specific cross-validation techniques and regularization methods to prevent overfitting.
• Strong skills in evaluating model performance using metrics like MSE, RMSE, MAE, MAPE, and R-squared.
• Familiarity with backtesting functionalities for validating model performance.
• Experience in model deployment, including serialization and deployment of models for real-time services.
• Strong communication skills for presenting findings and progress to stakeholders, using visualizations created with matplotlib, seaborn, or plotly.
• Proficiency in using Git for version control and collaboration.
• Major education in Data Science, Computer Science, or a related field IS A MUST. We do not accept people with other backgrounds.
• Certifications in deep learning are preferred.
• Excellent command of spoken and written English.
• Strong self-management, time management, and organizational skills.

• Ability to work under a structured management system while independently handling creative tasks.

   

What We Offer:

• Competitive remuneration package.
• Bonuses
• Professional mentorship and guidance from experienced team members.
• Opportunities for professional growth and continuous learning.
• A dynamic and collaborative work environment.
   

About DataObrii
DataObrii is a high-tech consulting firm specializing in data science, machine learning, and AI-augmented Internet of Things. Our team comprises experienced data scientists, python engineers, devops, hardware electrical engineers, and business analysts dedicated to delivering innovative, data-driven solutions that enhance business intelligence and efficiency. We emphasize continuous improvement, keeping up with current and emerging technologies, and delivering complete timely, effective solutions.

Our Values:

• Efficiency: We employ an agile approach to ensure timely delivery of high-quality solutions. This governs fast delivery cycles, quick and efficient solutions, iteratively going from PoC developments to fully enhanced production systems.
• Professionalism: Our commitment to excellence drives us to achieve success for our clients. This includes both technical and ethical proficiency required from all our employees.
• Creativity: We utilize design thinking to develop innovative solutions that address complex business challenges.
• Care: We invest time in understanding our clients' business models to provide tailored solutions that align with their objectives.
   

We are looking for a Data Scientist to join a risk modeling team within one of the leading banks in Ukraine. The team has been a benchmark in risk modeling for over 10 years, applying advanced Machine Learning techniques and global best practices.
 

We are open to considering candidates from Junior to Senior level, depending on experience and expertise.
 

In this role, you will develop ML solutions to minimize financial risks and optimize strategies for working with millions of customers.
 

Why Join the Team:

• Technology Stack: We use cloud solutions and modern development tools such as Amazon SageMaker, Amazon S3, Git, Confluence, etc.
• Scale: Working with large-scale datasets to support critical business decisions.
• Expertise: Risk models aligned with international standards and regulatory requirements.
• Professional Community: Strong Data Science community, regular internal workshops, participation in conferences, and sponsored learning.
• Automation: Proprietary system for managing the full ML lifecycle (from development to monitoring).
   

Key Requirements:

• 1+ year of experience in Data Science (experience in FinTech/Banking will be a strong advantage);
• Strong proficiency in Python for data analysis (NumPy, Pandas, SciPy, etc.) and experience optimizing SQL queries on large datasets;
• Hands-on experience with ML frameworks such as Scikit-learn and gradient boosting libraries (LightGBM, XGBoost, etc.);
• Experience with time series analysis and forecasting tools (Statsmodels, Prophet, etc.);
• Solid understanding of mathematics behind models (from linear regression to gradient boosting) and model evaluation techniques;
• Understanding of Big Data concepts and experience with version control tools (Git).
   

Nice to Have:

• Experience with Docker and/or MLflow;
• Knowledge of financial regulations (e.g., Basel III, IFRS 9).
   

Key Responsibilities:

• Credit Risk Modeling: Develop portfolio risk models (PD, LGD, EAD) in line with IFRS 9 requirements;
• Income & Solvency Forecasting: Build ML models to assess customer financial condition based on transactional activity;
• Credit & Behavioral Scoring: Develop classical and advanced scoring systems for automated decision-making across the customer credit lifecycle;
• Market Risk Analysis: Apply time series analysis and ML techniques to assess liquidity risk, forecast FX volatility, and model customer fund behavior;
• Fraud & Anomaly Detection: Build and maintain systems for detecting unusual transaction patterns in real time;
• ML Lifecycle: Participate in the full lifecycle of models — from idea and data collection to automated monitoring and retraining.
   

What We Offer:

• Opportunity to work in one of the leading banks in Ukraine;
• Official employment and 24+4 calendar days of vacation;
• Sick leave compensation;
• Competitive salary;
• Bonuses and performance-based incentives;
• Medical insurance;
• Corporate training and development programs;
• Remote work options;
• Financial support in critical situations.

If you’re a talented Data Scientist looking to be part of a fast-growing, innovative R&D team, shape the future of decision-making in business, work on cuttingedge technologies and vast amounts of global real-time data, affect billions of mobile users, and become an industry leader - then let’s talk! Start.io is a mobile data platform that enables organizations to uncover insights and make datadriven decisions that enhance strategies and drive growth. We are seeking a Senior Data Scientist to join our Data Science & Engineering team.

Responsibilities:

• Analyze large and complex data to discover hidden patterns and opportunities;
• Develop and own end-to-end highly scalable data pipelines;
• Develop state-of-the-art machine learning models, and algorithms and build solutions in monetization fields;
• Provisioning data models for real-time (online) processing;
• Shape new data products, and constantly improve the existing products;
• Collaborate with multiple teams including Product, BI, Analysts, DevOps, R&D and Marketing to lead and accomplish overall solutions;

• Oversee a complete release to production, including analyzing requirements, testing, monitoring and measuring results, multitasking, and quickly responding to critical issues.

   

Requirements:

• B.Sc./M.A/M.Sc. degree in Computer Science, Engineering, Math, Statistics, or other equivalent fields;
• 6 years as a Data Scientist - a strong background in ML concepts and models;
• Hands-on experience with Python, especially with data science ML libraries (regression & classification algorithms e.g. XGB or LGBM, recommendation system algorithms, etc.;
• Understanding of databases and SQL for data retrieval;
• Monitoring and alerting tools (e.g. Grafana, Kibana).

Will be a plus:

• Knowledge in the programmatic advertising landscape – DSPs, SSPs, exchanges – significant advantage;
• Experience with relational (e.g. Vertica, VoltDB) and non-relational (e.g. MongoDB) databases;
• Experience with PMML.

What we offer:

• Help and support from our caring HR team;
• 20 days of vacation;
• The exchange of experience and work with talented colleagues;
• Last but not least - valuable compensation for your efforts.

If you’re a talented Data Scientist looking to be part of a fast-growing, innovative R&D team, shape the future of decision-making in business, work on cuttingedge technologies and vast amounts of global real-time data, affect billions of mobile users, and become an industry leader - then let’s talk! Start.io is a mobile data platform that enables organizations to uncover insights and make datadriven decisions that enhance strategies and drive growth. We are seeking a Senior Data Scientist to join our Data Science & Engineering team.

Responsibilities:

• Analyze large and complex data to discover hidden patterns and opportunities;
• Develop and own end-to-end highly scalable data pipelines;
• Develop state-of-the-art machine learning models, and algorithms and build solutions in monetization fields;
• Provisioning data models for real-time (online) processing;
• Shape new data products, and constantly improve the existing products;
• Collaborate with multiple teams including Product, BI, Analysts, DevOps, R&D and Marketing to lead and accomplish overall solutions;
• Oversee a complete release to production, including analyzing requirements, testing, monitoring and measuring results, multitasking, and quickly responding to critical issues.

Requirements:

• B.Sc./M.A/M.Sc. degree in Computer Science, Engineering, Math, Statistics, or other equivalent fields;
• 6 years as a Data Scientist - a strong background in ML concepts and models;
• Hands-on experience with Python, especially with data science ML libraries (regression & classification algorithms e.g. XGB or LGBM, recommendation system algorithms, etc.;
• Understanding of databases and SQL for data retrieval;
• Monitoring and alerting tools (e.g. Grafana, Kibana).

Will be a plus:

• Knowledge in the programmatic advertising landscape – DSPs, SSPs, exchanges – significant advantage;
• Experience with relational (e.g. Vertica, VoltDB) and non-relational (e.g. MongoDB) databases;
• Experience with PMML.

What we offer:

• Help and support from our caring HR team;
• 20 days of vacation;
• The exchange of experience and work with talented colleagues;
• Last but not least - valuable compensation for your efforts.

Important: after confirming your application on this platform, you’ll receive an email with the next step: completing your application on our internal site, LaunchPod. So keep an eye on your inbox and don’t miss this step — without it, the process can’t move forward.

Why join us

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you! :)

About the role

We are looking for a Lead Data Architect to design and evolve healthcare data architecture, lead database modernization initiatives, and define interoperability strategy using HL7 and FHIR standards for a large-scale primary healthcare platform operating across Africa. You will design integration approaches for EMR, laboratory, pharmacy, and national health systems, working across SQL Server, PostgreSQL, and NoSQL databases in distributed system environments. The role includes mentoring engineers and supporting analytics, AI initiatives, and data governance practices.

What you will do

• Design and evolve healthcare data architecture and data models;
• Lead database modernization, optimization, and scalability initiatives;
• Define healthcare interoperability strategy using HL7 and FHIR;
• Design integration approaches for EMR, laboratory, pharmacy, and national health systems;
• Collaborate with engineering teams on architecture decisions;
• Support analytics, reporting, and future AI initiatives;
• Improve data quality, governance, and performance;

• Mentor engineers on database and integration best practices.

   

Must haves

• 7+ years of experience in Data Engineering, Data Architecture, or Solution Architecture;
• Strong experience with SQL Server and/or PostgreSQL;
• Experience with NoSQL databases;
• Enterprise data modeling experience;
• Experience with REST APIs and system integrations;
• Experience with distributed systems;
• Strong architecture and design skills;
• Experience with HL7 and/or FHIR;
• Experience designing enterprise-grade database schemas and healthcare data models;
• Strong understanding of scalable software architecture and performance optimization;
• Experience working in Agile/Scrum environments;

• Upper-intermediate English level.

   

Nice to haves

• Experience with AI/ML tools to accelerate software development and testing;
• Experience with healthcare, EMR, or EHR systems;
• Experience with analytics or data warehouse solutions;
• Experience in public health or other regulated industries.

The benefits of joining us

• Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps
• Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities
• A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands
• Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.

Meet Our Recruitment Process

Asynchronous stage – An automated, self-paced track that helps us move faster and give you quicker feedback:

• Short online form to confirm basic requirements
• 30–60 minute skills assessment via Codility – a platform founded in Poland that helps us provide quicker feedback and streamline this stage of the process.
• 5-minute introduction video

Synchronous stage – Live interviews

• Technical interview with our engineering team (scheduled at your convenience)
• Final interview with your future teammates
•  

If it’s a match — you’ll get an offer!

Mirko Solutions is an international IT company specializing in web and mobile development for clients across the US, Canada, EU, and Australia. We are growing rapidly and are looking for a Middle+/Senior Data Scientist to join our team and work on data-driven solutions, advanced analytics, and business intelligence projects.

This is currently a part-time opportunity with the possibility of transitioning to a full-time position in the future based on project needs and successful collaboration.

Job Requirements:

• 5+ years of professional experience in Data Science, Machine Learning, or Advanced Analytics
• Strong hands-on experience with Python for data analysis, modeling, and automation
• Proven experience working with Power BI for data visualization, reporting, and building interactive dashboards
• Strong knowledge of statistical analysis, predictive modeling, and machine learning algorithms
• Experience with data preprocessing, feature engineering, model evaluation, and optimization
• Solid understanding of data pipelines and working with large datasets
• Experience with SQL and relational databases
• Experience deploying and maintaining data science solutions in production environments
• Understanding of cloud platforms (AWS/GCP/Azure) and modern data ecosystems is a plus
• Strong analytical thinking and ability to translate business requirements into data-driven solutions
• Excellent collaboration and communication skills in English
• Ownership mindset, curiosity, and ability to work independently in a fast-paced environment

Responsibilities:

• Develop and implement data science solutions to support business decision-making
• Analyze complex datasets, identify trends, and provide actionable insights
• Build predictive models and machine learning solutions based on business needs
• Perform data preparation, cleaning, transformation, and feature engineering
• Create and maintain interactive dashboards and reports using Power BI
• Develop data analysis workflows and automation scripts using Python
• Collaborate with engineering, product, and business teams to define analytical approaches and deliver impactful solutions
• Monitor model performance and improve existing data-driven solutions
• Contribute to data quality improvements, analytics processes, and best practices
• Document methodologies, models, and analytical results

Nice to have:

• Experience with machine learning frameworks such as scikit-learn, TensorFlow, PyTorch, XGBoost
• Experience with cloud data platforms and services (AWS SageMaker, Azure ML, Google Vertex AI, Databricks)
• Experience with data visualization libraries (Matplotlib, Seaborn, Plotly)
• Knowledge of Big Data technologies (Spark, Hadoop)
• Experience with MLOps practices, model versioning, and deployment workflows
• Familiarity with LLMs, Generative AI solutions, or NLP approaches

We provide the following for our employees:

• Competitive salary according to qualification
• Comfortable working environment
• Experienced colleagues
• Opportunity to work on interesting international projects
• Regular performance reviews
• Professional growth opportunities
• Friendly atmosphere and care for the comfort of professionals

About the company: United Tech is a global IT product company shaping the future of real-time social connection. With millions of users across North America, Europe, LATAM, and MENA, we build next-gen mobile and web apps for live-streaming and social networking. Our platforms enable connection at scale fast, interactive, and deeply engaging. The market is projected to exceed $206B by 2030, and we are already leading the evolution. Founded in Ukraine, scaling worldwide
 

About your role: In this role, you will directly influence product growth and monetization by improving Recommendation Systems for gifts and coins. You’ll work end-to-end on ML solutions — from defining the Data Science roadmap and running experiments to deploying production-ready models — while collaborating closely with Product Managers, Analysts, and Engineers. The role offers a combination of hands-on machine learning, recommendation systems, MLOps, and strategic ownership in a fast-paced product environment where your work will have visible business impact.

In this role, you will

• Create, develop, and improve machine learning models to enhance business performance and product effectiveness
• Collaborate closely with cross-functional teams, including Product Managers, Analysts, and Engineers, to deliver innovative ML-driven features and improvements
• Apply expertise in machine learning algorithms, data structures, and optimization techniques to improve model accuracy, scalability, and efficiency
• Implement and maintain MLOps best practices for model deployment, monitoring, retraining, and maintenance in production environments
• Investigate, troubleshoot, and resolve technical issues related to machine learning models, data pipelines, and infrastructure
• Stay up to date with the latest advancements, technologies, and best practices in machine learning, artificial intelligence, and data science

It’s all about you

• 4+ of Machine learning and deep learning on tabular data, Recommendation systems. 
• 4+ years of software development experience in Python with experience working with ML and DL
• Experience in designing a data science roadmap and the leading technical execution of the project
• Experience with Cloud development AWS/GCP
• Experience of deploy API models on Dev/Prod environment
• Practical understanding of A/B tests process
• Practical understanding of the mathematics behind modern machine learning, linear algebra, and statistics.
• Extensive SQL knowledge

What we offer

Care and support: 

• 20 paid vacation days, 15 sick days, and 6 additional days off for family events
• Up to 10 additional days off for public holidays
• 100% medical insurance coverage
• Sports and equipment reimbursement
• Team building events, corporate gifts, and stylish merch
• Maternity recovery support allowance 
• Financial and legal support
• Position retention and support for those who join the Armed Forces of Ukraine
• Participation in social initiatives supporting Ukraine
   

Comfortable working environment:

• Work from our Kyiv hub or remotely with a flexible schedule 
• Modern equipment or depreciation of your own tools
   

Investment in your future:

• Collaborate with a highly-skilled team of Middle & Senior professionals, sharing practical cases and expertise in the social networking niche
• 70% of our heads and leads have grown into their roles here – so can you!
• Performance-oriented reviews and Individual Development Plans (IDPs)
• Reimbursement for professional courses and English classes
• Corporate library, book club, and knowledge-sharing events
   

Hiring process

• Intro call
• Technical Interview
• Final Interview
• Reference check
• Offer

Are you a Data Scientist with a love of LLMs, generative AI?

We are looking for a passionate Data Scientist to implement AI solutions aimed at achieving business goals.

This role offers the opportunity to work on cutting-edge AI adoption projects that helps to improve current business processes.

You'll be a great fit if you have:
• Strong Python Experience (1 year +);
• Experience with LLM , Diffusion models (1 year +);
• Knowledge of Prompt engineering;
• Experience with Gen AI-related technologies such as LangChain and RAG;
• Experience with Neural Networks (Optional) ;
• Experience with NLP , Predictive analytics and Machine learning;
• Experience with Pandas;
• Experience with SQL, including experience with large datasets;
• Strong experience in statistics;

What you'll do:
• Develop AI agents that utilize LLM, RAG and langchain approach;
• Implement LLM and Diffusion models to boost business productivity;
• Utilize LLM (LLM Vision) to improve object detection, text classification and extraction;
• Create forecasting, recommendation, and classification models;
• Transform business challenges to AI applications;

We ensure your growth with:

• Competitive salary fixed in USD

• Flexible working schedule and fully remote work format

• Paid vacation days and sick leave days 

• Personal and professional development opportunities

• Participation in building innovative projects from scratch using modern technologies

• Team-building activities and corporate events

• English classes and educational events.

Data Science UA is a service company with deep expertise in AI and Data Science. Our story started in 2016 with the first Data Science UA Conference in Kyiv, and since then, we’ve built one of the largest AI communities in Europe.

About the role and client:
We are looking for Data Operations Lead to the clients team - a leading Ukrainian manufacturer of autonomy technologies for drones. The role mission is to ensure the full data lifecycle: from strategic project planning to quality assurance and validation of final deliverables.

Responsibilities:
- Planning & Prioritization: Plan and prioritize dataset projects in alignment with the ML team's roadmap and product goals.
- Synthetic Data Generation Ownership: Own the synthetic data generation direction — coordinate pipeline development, prioritize scenarios, and control the quality of generated data.
- Manual Data Annotation Team Ownership: Lead the manual data annotation team — handle hiring, onboarding, performance reviews, tool training, and quality control.
- Team Coordination: Coordinate dataset engineers and the annotation team — assign tasks, track progress, and balance workloads.
- Requirements Alignment: Align dataset requirements with ML engineers — translate ML model training needs into dataset specifications and definition of done (criteria of readiness).
- Capacity & Resource Management: Forecast capacities, reallocate workloads, and resolve blockers.
- Project-Level Quality Tracking: Monitor project-level metrics of dataset deliverables and identify systemic issues.
- Vendor Management: Manage external annotation partners — handle vendor evaluation, contracting, and quality control.
- Processes & Standards Maintenance: Maintain workflows, documentation, and SLAs for working with datasets.
- Reporting: Report on dataset projects to leadership and the ML team — sharing status, progress, risks, and blockers.
- Continuous Improvement: Continuously optimize processes to improve annotation throughput, cycle times, and reduce error rates.
- Platform Support: Support the dataset catalog platform from a process and organizational perspective.

Requirements:
- 2+ years of experience in a similar role.
- People Management: Proven experience in direct management — hiring, developing, and building workflows for manual annotators.
- Data & ML Literacy: Solid understanding of the ML lifecycle and experience working with data (knowledge of data types, structures, and processing methods).
- Synthetic Data: Understanding of synthetic data generation principles and automated data collection approaches.
- Analytical Skills: Ability to forecast capacity, identify process bottlenecks, and propose optimization solutions.

Nice to have:
- Knowledge of the MilTech / DefTech market.

BETER is a rapidly growing product company. We create competitive content supplemented with analytics. For more than 5 years, we have been organizing sports tournaments, broadcasts, and developing our own sports community. We hold 45,000+ events per month in esports and traditional sports, and our products are represented in 150+ countries worldwide.

We are looking for a hands-on Data Science Tech Lead to join our team and drive the development of sports analytics and prediction products. This role combines deep technical expertise in machine learning and mathematical modeling with team orchestration and delivery ownership.

You will work closely with the Engineering Manager and lead a team of 4 Data Science Engineers, helping transform business needs and production challenges into scalable data science solutions.

Responsibilities:

• Collaborate with the Engineering Manager to coordinate and support a team of 4 Data Science Engineers
• Collect and analyze business requirements, production issues, and product needs, transforming them into actionable data science tasks and backlog
• Analyze large volumes of sports, esports, and trading data
• Develop and improve sports prediction models using statistics and machine learning techniques
• Conduct, automate, and evaluate data-driven experiments
• Integrate mathematical and ML models into production workflows
• Participate in hands-on development and coding activities
• Perform code reviews and maintain high engineering and data science quality standards
• Ensure efficient execution and delivery of data science initiatives within the team

Requirements:

• Previous experience in a Tech Lead or team leadership role
• Strong hands-on programming skills in Python
• Advanced knowledge of databases and data processing
• Strong expertise in machine learning, statistics, and probability theory
• Experience building and deploying mathematical or predictive models
• Upper-Intermediate+ level of English
• Ability to balance technical leadership with hands-on engineering work

What we’re looking for:

This is primarily a hands-on engineering role. The main focus is building mathematical models, writing production-level code, and delivering real business impact through data science solutions.

At the same time, the role requires strong coordination skills — the ability to distribute work effectively within the team, support engineers, and ensure successful delivery together with the Engineering Manager.

Successful probation expectations:

During the probation period, we expect the successful delivery of a sports analytics or modeling product through:

• effective team orchestration,
• hands-on contribution to development,
• and high-quality execution of data science workflows.

Ideal candidate profile:

We would love to meet someone who is:

• proactive in communication and information gathering,
• focused on data-driven decision making,
• detail-oriented and demanding when it comes to production quality and best practices.

Also relevant:

• High-load real-time data environments, such as fintech, gaming, marketing analytics, computer vision, or similar domains, working with large-scale data streams.

We offer:

• Ability to work remotely
• Competitive and timely payment for services
• Flexible work schedule
• Personal mentoring and coaching
• Team building and corporate events
• 100% paid sick leave
• 20 working days of paid vacation
• Paid child care leave

Equals5 helps pharmaceutical companies run precisely targeted ad campaigns on social platforms by identifying healthcare professionals and the consumer signals that reach them. The Identity team builds the data, scoring, and targeting systems that make this possible.

We are looking for a Data Analyst  to join the Identity team at Equals5. This is not a standard analyst role. We are building a dynamic identity resolution system where AI is deeply integrated — both as a productivity multiplier and as a core component of our data processing logic for identity resolution and LLM-based scoring.

We run enrichment against 70+ TB of data, apply AI and LLM-based scoring on top, and process around 20 million enrichment operations per day across hundreds of thousands of records.

The analytical challenges ahead are substantial: how to measure the quality of AI-driven scoring, how to validate that a change makes the system better, how to know where our money and time deliver the most value, and how to turn the questions our internal teams bring in into fast data-backed answers. You will own this side of the business, working daily alongside engineers and the product lead to turn these challenges into decisions that ship.

The main part of the role is not building dashboards — it is the data work that makes a meaningful dashboard possible in the first place. Concretely, you will be:

• Looking at data from multiple vendors side by side and deciding what to trust.
• Reconciling entities across sources that have different shapes and quality.
• Proposing and validating the logic that matches and scores them.
• Defining metrics and ground truth for questions nobody has asked before.
• Tracing why numbers don't line up across partial and sometimes contradictory sources.

Dashboards and visualizations are part of how findings get communicated, but they come at the end — the surface of the work, not its core. Most of your time is spent on what sits underneath: methodology, judgment calls on data quality, and shaping how the domain understands its own numbers.

Responsibilities

• Measurement & Evaluation Foundations: Define how we measure what matters — data quality, the accuracy of our AI scoring, how many records actually get matched to usable signals, cost per outcome. Build the feedback loops that tell us whether a change makes the system better or worse.

• Scoring Intelligence (co-owned with engineers): Partner with the engineering team on the LLM-based scoring system. You will build the evaluation framework for AI scoring, run experiments comparing prompts, models, and approaches against a baseline, and make data-backed calls on where we invest next. Our AI scoring system is actively evolving — you will shape how we measure and improve it.

• Client-related Analysis: Own the analytical side of the work that internal sales and media-buying teams bring in from pharma clients — how reachable a target audience is, how good the data looks, why a campaign performed the way it did. You turn their questions into data-backed answers they can use. Identity is a product core; the analyst works with internal teams, not with clients directly.

• Cost and Value Analysis: Turn cost and value into product decisions. Which data sources and enrichment scenarios pay off, where we overspend, what to cache, what to cut. We operate a mix of free owned data and paid external providers — the decisions have real dollar impact.

• Active AI Usage: Use Claude Code and modern AI engineering tools to multiply your own output. Automate the repetitive parts of analysis so you can focus on the decisions. We provide Claude Code licenses and expect active daily use.

• Data Quality Response: When pipeline output drifts, a provider degrades, or upstream data shifts, you notice first, diagnose the root cause, and drive the fix. You treat data quality as a product, not a ticket queue.

Requirements

• 5+ years as a Data Analyst, Analytics Engineer, or Data Scientist in a product team (not consultancy, not BI-only roles).
• Advanced SQL at TB scale — BigQuery, Snowflake, or equivalent warehouse. You can read and write complex queries on tens of terabytes without someone pre-modelling the data for you.
• Python for analysis at a working level — pandas, Jupyter, or modern equivalents. Comfortable putting together a small script or helper when an existing tool doesn't cover your case.
• Built measurement or evaluation frameworks from scratch for systems that had no baseline. You are comfortable defining what and how to measure, not consuming someone else's KPI.
• Comfort with probabilistic systems. You understand that noise is inherent and 100% accuracy is not the goal — scoring, matching, ranking.
• AI-native workflow. You already use Claude Code, ChatGPT, Copilot, or similar AI tools daily and integrate them into your analytical process.
• English: B2+ (Upper-Intermediate) or higher.

Strong plus 

• LLM evaluation experience — A/B testing AI-powered features, output scoring, prompt iteration with measurable outcomes.
• Identity resolution / identity graph experience — adtech, martech, or customer data platform context (LiveIntent, LiveRamp, Epsilon, Experian Marketing, Acxiom, Merkle, or similar).
• Healthcare or pharma data — working with NPI, HCP-level data, healthcare taxonomies, pharma targeting.

Nice to have

• Experience running controlled experiments on data pipelines.
• Prompt engineering or structured LLM prompt design.
• Prior work in AI-first product companies.

What We Offer

• Fully remote with flexible hours, with working overlap in CET ±2 hours for syncs.
• AI-Native Environment: We provide licenses for Claude Code and encourage using the bleeding edge of AI tech — both for daily work and as part of product logic.
• High-Impact Role: You will directly shape how we identify, score, and reach healthcare professionals — the core business of our domain.
• Small team, direct impact: You will work directly with Product and Engineering leads — no layers between you and the people making decisions.
• No Bureaucracy: Fast decisions, no legacy processes, focus on results.

Are you a Data Scientist with a love of LLMs, generative AI?

We are looking for a passionate Data Scientist to implement AI solutions aimed at achieving business goals.

This role offers the opportunity to work on cutting-edge AI adoption projects that helps to improve current business processes.

You'll be a great fit if you have:
- Strong Python Experience (1 year +);
- Experience with LLM , Diffusion models (1 year +);
- Knowledge of Prompt engineering;
- Experience with Gen AI-related technologies such as LangChain and RAG;
- Experience with Neural Networks (Optional) ;
- Experience with NLP , Predictive analytics and Machine learning;
- Experience with Pandas;
- Experience with SQL, including experience with large datasets;
- Strong experience in statistics;

What you'll do:
- Develop AI agents that utilize LLM, RAG and langchain approach;
- Implement LLM and Diffusion models to boost business productivity;
- Utilize LLM (LLM Vision) to improve object detection, text classification and extraction;
- Create forecasting, recommendation, and classification models;
- Transform business challenges to AI applications;

We ensure your growth with:

- Great networking opportunities with international clients, challenging tasks;

- Building interesting projects from scratch using new technologies;

- Personal and professional development opportunities;

- Competitive salary nominated in USD;

- Paid vacation and sick leaves;

- Flexible work schedule;

- Friendly working environment with minimal hierarchy;

- Team building activities, corporate events.

At Fozzy Group, we are building the next generation of AI-powered personalization products that help millions of customers discover relevant products, simplify shopping, and create a seamless omnichannel experience.
 

As a Senior Data Scientist, you will own the design and delivery of machine learning solutions that power personalized customer experiences across our digital platforms. You will architect, build, and optimize large-scale recommendation systems end to end — from research and prototyping to production and measurable business impact on customer engagement, conversion, basket growth, and retention.

You will drive a broad portfolio of personalization products, including Recommendations, Similar Products, Product Substitutions, Bundles, Cross-sell, Upsell, and Next Best Action, partnering closely with Product Managers and Software Engineering teams, and mentoring less experienced data scientists along the way.
 

Key Responsibilities

• Own the end-to-end design, development, and deployment of large-scale recommendation systems for personalized product discovery.
• Own execution of personalization strategy across multiple customer touchpoints, including Home Page, Product Detail Pages, Basket, Search, Checkout, CRM campaigns, and other digital experiences.
• Architect ranking models that optimize recommendations across multiple, often competing business objectives: relevance, conversion, diversity, novelty, customer satisfaction, and revenue.
• Design customer and product representations using embeddings, representation learning, and graph-based machine learning techniques.
• Lead the development of customer preference and Next Best Action models using behavioral, transactional, and contextual data.
• Define experimentation strategy: design, execute, and analyze A/B tests to rigorously evaluate the business impact of personalization initiatives, applying causal inference where appropriate.
• Drive continuous improvement of recommendation quality using collaborative filtering, content-based methods, hybrid recommenders, learning-to-rank, and deep learning approaches — choosing the right method for each problem.
• Set standards for scalable feature engineering pipelines and reusable ML components, and drive their adoption across the team.
• Establish best practices for deploying, monitoring, and maintaining ML models in production, ensuring reliability, scalability, and reproducibility.
• Partner with Product, Engineering, Commercial, and Analytics leadership to translate business challenges into a roadmap of scalable AI products.
• Mentor middle and junior data scientists through code and design reviews, technical guidance, and knowledge sharing.
   

Preferred Qualifications

• 5+ years of experience in Data Science / Machine Learning, including proven experience building production-grade Recommendation Systems at scale.
• Deep understanding of Learning-to-Rank algorithms, ranking optimization, and multi-objective optimization.
• Expert-level knowledge of Collaborative Filtering, Content-Based, and Hybrid Recommendation models, and when to apply each.
• Strong background in customer modeling, preference learning, and representation learning.
• Experience with Graph Machine Learning or Graph Neural Networks is a plus.
• Advanced hands-on experience with deep learning frameworks such as PyTorch or TensorFlow.
• Proven track record of building scalable ML pipelines and production MLOps workflows.
• Strong expertise in experimentation, A/B testing, and causal inference, including experiment design for complex product ecosystems.
• Excellent SQL and Python skills; experience with Spark or distributed data processing frameworks is a plus.
• Demonstrated ability to lead technical initiatives, influence cross-functional stakeholders, and mentor other data scientists.
   

What We Offer 

• Competitive salary.
• Professional & personal development opportunities.
• Being part of dynamic team of young & ambitious professionals.
• Corporate discounts for sport clubs and language courses.
• Medical insurance package.

Fozzy Group is one of the largest trade industrial groups in Ukraine and one of the leading Ukrainian retailers, with over 700 outlets all around the country. It is also engaged in e-commerce, food processing & production, agricultural business, parcel delivery, logistics, and banking.   
 

At Fozzy Group, we are developing a next-generation Decision Support System that connects operational, commercial, and investment data to optimize financial effectiveness and drive guest experience. As a Data Scientist you will own the measurement layer to derive Initiative & Investment Performance Insights. The role 

is organized around three streams: 

• Effect Measurement & Causal Inference: quantify the true incremental impact of initiatives using A/B testing and quasi-experimental methods. Measure uplift in purchase frequency, guest spend, average check, and retention against properly designed control groups, and form clear conclusions on whether an initiative works and is worth its cost. 

• Driver & Heterogeneity Analysis: identify the most significant factors of project performance using ML: guest profile structure and dynamics, technology presence, assortment, distance to competitors – so the business can assess project potential per store, forecast effects, and scale more effectively. 

• Self-Service Validation & Monitoring: build reusable, automated frameworks for effect validation and monitoring that let Finance and business owners get verified answers on demand, with full source transparency and reproducibility.
You will join a cross-functional team to design and implement data-driven decision module that directly influence financial outcomes. 

Job Responsibilities 

• Design and run experiments (A/B tests) and quasi-experiments (difference-in-differences, synthetic control, propensity score matching), and apply causal ML to estimate the incremental and heterogeneous effects of operational, commercial, and investment initiatives. 

• Build uplift / heterogeneous-treatment-effect models to learn which guests, segments, and stores respond most, and quantify effects on key metrics – purchase frequency, share-of-wallet / guest spend, average check, CLV, and retention (via survival models) – for pilot versus control groups. 

• Develop interpretable driver models (gradient boosting with SHAP, causal forests) that explain project performance, and rank the factors with the highest impact on results. 

• Build store-level potential-scoring and effect-forecasting models – probabilistic and hierarchical forecasting, transfer learning and store embeddings to borrow signal across the network – to guide and prioritize scaling decisions. 

• Design adaptive early-stop logic using Bayesian sequential testing, multi-armed bandits, and change point detection, to reallocate or halt rollouts as soon as the economic signal turns marginal. 

• Translate financial and commercial questions into statistically rigorous measurement designs, and connect statistical results to economic value (incrementality, ROI, payback). 

• Build SQL and Python pipelines, reusable feature sets / a feature store, and a self-service experimentation framework. 

• Productionize and monitor models (MLOps) – drift detection, automated validation, reproducibility, and source transparency. 

• Partner with Finance, Investment, Commercial, and Operations teams to deliver verified, decision ready insights. 
 

Requirements 

• Bachelor’s Degree in Mathematics / Quantitative Economics / Econometrics / Statistics / Computer Sciences / Finance; 

• At least 2 years working experience on Data Science; 

• Strong foundation in Statistics, Causal Inference, and Experimental Design – A/B testing, Hypothesis Testing, Power Analysis; 

• Proven experience with SQL (Window functions, CTEs, joins) and Python; 

• Expertise in Machine Learning, Time Series Analysis; 

• Ability to work independently and decompose complex problems. 
 

Preferred 

• Experience with Airflow, Docker, or Kubernetes for Data Orchestration; 

• Practical experience with Amazon SageMaker: training, deploying, and monitoring ML models in a production environment; 

• Knowledge of Reporting and Business Intelligence Software (Power BI, Tableau, Looker); 

• Ability to design and deliver packaged analytical/ML solutions. 
 

What We Offer 

• Competitive salary; 

• Professional & personal development opportunities; 

• Being part of dynamic team of young & ambitious professionals; 

• Corporate discounts for sport clubs and language courses; 

• Medical insurance package.

Fozzy Group is one of the largest trade industrial groups in Ukraine and one of the leading Ukrainian retailers, with over 700 outlets all around the country. It is also engaged in e-commerce, food processing & production, agricultural business, parcel delivery, logistics and banking.
 

The Foodtech team is looking for a Data Scientist to develop the Operational Analytics function for a fast growing food delivery business. In this role, you will focus on time series forecasting, regression modeling, simulation modeling, and end-to-end machine learning pipelines to support resource planning and operational decision-making.

You will be responsible for developing simulation-based models that serve as a foundation for a digital twin of operational processes, enabling scenario analysis, stress testing, and what-if simulations for capacity planning and operational optimization.

You will work closely with product, engineering, and operations teams to transform data into measurable business impact through production-ready ML and simulation solutions.
 

Job Responsibilities:

• Develop and implement time series forecasting models for resource planning (demand, capacity, couriers, delivery slots, operational load);
• Build regression and machine learning models to explain key drivers and support operational decisions;
• Apply a wide range of time series approaches from classical models (SARIMA, ETS, Prophet) and ML models (GB) to modern Deep Learning models (LSTM, Temporal CNNs, Transformers for TS);
• Design, build, and maintain end-to-end automated ML pipelines, deploy and operate models in production using AWS SageMaker;
• Orchestrate training and inference workflows with Apache Airflow;
• Analyze large-scale operational datasets and convert results into insights, forecasts, and actionable recommendations;
• Collaborate with product managers, engineers, and operations teams to define business problems and validate analytical solutions;
• Monitor model performance, forecast stability, and business impact over time.
   

Requirements:

• Bachelor’s Degree in Mathematics / Engineering / Computer Sciences / Quantitative Economics / Econometrics;
• Strong mathematical background in Linear algebra, Probability, Statistics & Optimization Techniques;
• At least 2 years working experience on Data Science;
• Experience of the full cycle of model implementation (data collection, model training and evaluation, model deployment and monitoring);
• Ability to work independently, proactively, and to decompose complex problems into actionable tasks.
   

Skills:

• Strong proficiency in Python with solid application of object-oriented programming (OOP) principles (modular design, reusable components, maintainable code);
• Solid experience in time series forecasting and regression modeling;
• Practical knowledge of:o Classical and ML forecasting techniques;
  o Statistical methods (hypothesis testing, confidence intervals, A/B testing);
• Advanced SQL skills (window functions, complex queries);
• Experience building automated ML pipelines;
• Understanding of MLOps principles (model versioning, monitoring, CI/CD for ML).
   

Nice to have:

• Hands-on experience with AWS SageMaker (training jobs, endpoints, model registry);
• Experience with Apache Airflow for data and ML workflow orchestration;
• Knowledge of Reporting and Business Intelligence Software (Power BI, Tableau);
• Experience working with large-scale production data systems.
   

What We Offer:

• Competitive salary;
• Professional & personal development opportunities;
• Being part of dynamic team of young & ambitious professionals;
• Corporate discounts for sport clubs and language courses;
• Medical insurance package.