Jobs Data Scientist

Dataforest is looking for a Data Scientist to join an interesting software development project in the field of Cybersecurity. Our client's platform offers Identity Insights drives real-time, multi-contextual digital forensics to protect new account opening workflows and expose fake accounts already in a customer database.

    Required Qualifications

• 2+ years of experience working with large-scale, complex datasets.
• Experience with imbalanced data.
• High proficiency in Python for data analysis, feature engineering and modeling.
• Expertise in exploratory data analysis and preparing clean, structured datasets for model development.
• Hands-on experience with AI/ML techniques:
• Supervised (eg. gradient boosting, decision trees, etc.)
• Unsupervised (eg. anomaly detection, clustering, etc.)
• Familiarity with basic statistical concepts and model evaluation metrics (eg. precision, recall, ROC-AUC).
• Upper-intermediate (B2) or higher level of English.
  
  Nice to Have
• Hands-on experience in the fraud/risk domain.
• Experience with Databricks (including Pyspark) for data processing, experimentation, and model development.
• Experience in MLflow library for experiment tracking and model lifecycle management.
• Experience working with diverse data sources (e.g., behavioral, device, or transactional data) and deriving meaningful features.
• Experience assessing data quality and validating new data sources in production environments.

     Key Responsibilities

• Analyze large-scale transaction datasets to identify fraud patterns and risk signals.
• Develop and validate ML models for risk scoring and fraud detection/classification.
• Support deployment of models into production environments by collaborating with the development team.
• Monitor model performance, conduct regular evaluations, analyze the results.
• Perform feature engineering to continuously improve model performance.
• Collaborate with the client on R&D efforts, including exploratory data analysis, feature development, and testing new approaches.

     We offer

• Great networking opportunities with international clients, challenging tasks;
• Building interesting projects from scratch using new technologies;
• Personal and professional development opportunities;
• Competitive salary fixed in USD;
• Paid vacation and sick leaves;
• Flexible work schedule;
• Friendly working environment with minimal hierarchy;
• Team building activities and corporate events.

Dataforest seeks a Data Science Tech Lead/Team Lead to join a friendly, supportive team. We are Data Engineering company working on AI adoption in different industries.

We are looking for a person who likes challenges. This position offers the possibility of working as a Manager, however, to keep track of ongoing changes in the AI field and participate in AI projects.

As a Tech Lead/Team Lead, you will collaborate with the CEO and CTO to define proper development processes, run an R&D practice, participate in pre-sale, and lead ongoing AI projects.

Skills Requirements:

• 5+ years of experience in Data Science\Data engineering field;

• 4+ years of experience with Python;

• Strong management and leadership skills;

• Knowledge of data algorithms and data structures is a MUST;

• Experience with business analysis and project management;

• Knowledge of DS and Machine learning algorithms.

• Experience with LLM, RAG , Langchain;

• Experience with Databricks, Snowflake (Optional);

• Knowledge of cloud solutions: AWS/Azure/GCP (Optional);

• Experience in multithreading/multiprocessing approaches;

• Proficiency with Docker, Kubernetes, and CI/CD pipelines;

• Previous experience in a Team Lead role;

Key responsibilities:

• Manage Data science department;

• Perform code review, and data scientists assessment;

• Develop DS Architecture;

• Participate in pre-sale activities;

• Lead a data science projects;

• Write clean and well-structured code that is easy to read and maintain;

• Participate in decision-making processes related to design architecture, solution development, architectural, and code reviews;

• Develop high-load solutions;

• Conduct R&D work with new technology;

• Maintain high-quality coding standards within the team.

We offer:

• Great networking opportunities with international clients, challenging tasks;

• Building interesting projects from scratch using new technologies;

• Personal and professional development opportunities;

• Competitive salary fixed in USD;

• Paid vacation and sick leaves;

• Flexible work schedule;

• Friendly working environment with minimal hierarchy;

• Team building activities and corporate events.

Our Enterprise Banking client is enhancing their Regulatory Reporting Value Stream and seeks a strategic Data Steward to own data governance, ensure compliance, and maintain the integrity of critical financial data. You will serve as the primary liaison between business stakeholders and technical teams to ensure data accuracy across products, systems, and processes.

Core Responsibilities

• Data Governance Leadership: Own and drive end-to-end data governance and quality frameworks; ensure full compliance with internal standards and external regulatory requirements.
• Architectural Stewardship: Maintain business glossaries, metadata repositories, and data quality rules; design robust data mappings and transformation logic.
• Requirements Engineering: Translate complex business/regulatory needs into clear functional specifications for engineering teams.
• Quality Remediation: Perform root cause analysis on data quality incidents and coordinate cross-functional remediation efforts.
• Strategic Insights: Develop KPIs and performance dashboards to provide stakeholders with actionable data trends and business intelligence.

What We Need

• Expertise: Significant professional experience in Data Governance, Data Stewardship, or Technical Business Analysis.
• Domain Knowledge: Solid grounding in banking/financial services products and regulatory reporting workflows.
• Technical Proficiency: Advanced SQL skills for large-scale data analysis, profiling, and structural mapping; deep understanding of data warehousing principles.
• Collaboration: Proven ability to act as the "connective tissue" between business units and IT delivery teams.
• Tooling: Proficiency in JIRA, Confluence, and the MS Office suite.

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.

Established clinical trials company in USA is seeking a Ukraine-based statistical programmer to join the team.  Company has been working in Ukraine since 2012.

Candidate should have a strong history of working with SAS, CDISC and SDTM.  In the company's own words:

"Candidate will create the TLFs for our client.  They are the core statistical outputs that transform raw patient data into regulatory-ready formats to prove a drug's safety and efficacy. These deliverables are generated by statistical programmers based on a predefined Statistical Analysis Plan (to be provided by the customer's biostatistician) and reviewed by biostatisticians. They are essential for medical writers, who use them to write Clinical Study Reports (CSRs) for regulatory bodies like the FDA and EMA."

Position is part-time and can be based anywhere in Ukraine.

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.

Skills requirements:
• 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;

Key responsibilities:
• 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 offer:

• 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.

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.

Skills requirements:
• 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;

Key responsibilities:
• 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 offer:

• 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.

Role Overview

We are a systematic prop trading firm operating at the intersection of CeFi and DeFi, with infrastructure deployed across 50+ exchanges and 20+ chains.
 

We are looking for a Senior Quantitative Researcher & Algorithmic Strategist to join the trading team. In this role, you will fully own the lifecycle of trading strategies — from research and backtesting to production deployment and optimisation.
 

This is a high-autonomy, high-impact position with direct collaboration with the founding team.
 

Key ResponsibilitiesStrategy Development

• Develop proprietary alpha signals or adapt existing strategies
• Design, backtest, and forward-test systematic trading strategies
• Conduct statistical validation (walk-forward, out-of-sample, regime analysis)
• Analyse capacity, decay, and correlation within the portfolio
• Prepare research documentation and performance reports
   

Engineering & Deployment

• Translate research into production-grade code (Python / C++ / Rust)
• Build algorithms for CEX market-making programs (Binance, OKX, Bybit)
• Improve order book logic (spread, inventory, execution efficiency)
• Integrate strategies into low-latency infrastructure
• Monitor live performance and conduct post-trade analysis
   

Market Microstructure & Execution

• Optimize fill rates, slippage, and latency
• Work with order book dynamics and execution logic
• Improve rebate capture and maker program performance
   

RequirementsHard Requirements (Must-have)

• Proven live trading track record (real P&L, not only backtests)
• Strong knowledge of crypto market microstructure
• Production-level coding in Python
• Working knowledge of C++ or Rust (preferred)
• Strong quantitative background (statistics, probability, time-series)
• Experience with exchange APIs (REST/WebSocket)
• Ability to own strategies end-to-end independently
   

Nice to Have

• Experience in prop trading / HFT / crypto quant firms
• Market-making algorithm experience
• Experience with CEX maker programs
• Familiarity with DEX / on-chain trading / MEV
• Experience in arbitrage strategies (CeFi–DeFi / cross-venue)
• Risk management systems (PnL limits, volatility sizing)
   

Academic Background

• Degree in Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or similar
• Practical track record is prioritized over formal education
   

What We’re Looking For

• Strong ownership mindset over strategies and results
• Ability to explain and defend your edge
• Deep understanding of why strategies work (and fail)
• Attention to execution details (fees, latency, fills)
• Intellectual honesty and data-driven thinking
• Collaborative, non-ego-driven approach
   

Compensation

• Base Salary: Competitive (USD / stablecoin)
• Performance Bonus: P&L-based allocation (high-water mark model)
• Capital Allocation: Up to $100M+ per strategy (based on performance)
• Infrastructure: Full access to trading stack (50+ venues, low latency)
• Format: Remote-first, high autonomy
   

What We Offer

• Ready-to-use trading infrastructure (no need to build from scratch)
• Direct access to decision-makers
• Fast capital deployment
• Exposure to cutting-edge crypto markets (CEX + DEX)
• Collaborative research environment
• Flat team structure
   

Hiring Process

1. Call with Recruiter (30 min) — background and strategy discussion
2. Team interview (60 min) — strategy walkthrough
3. Final C-level Interview (30 min) 

Quantum is a global technology partner delivering high-end software products that address real-world problems. 

We advance emerging technologies for outside-the-box solutions. We focus on Machine Learning, Computer Vision, Deep Learning, GIS, MLOps, Blockchain, and more.

Here at Quantum, we are dedicated to creating state-of-the-art solutions that effectively address the pressing issues faced by businesses and the world. To date, our team of exceptional people has already helped many organisations globally attain technological leadership.

We constantly discover new ways to solve never-ending business challenges by adopting new technologies, even when there isn't yet a best practice. If you share our passion for problem-solving and making an impact, join us and enjoy getting to know our wealth of experience!

About the position

Quantum is expanding its team in Central Europe and is looking for talented Data Science Engineers to join us. Our projects span multiple domains, including data analysis, fintech, computer vision, image processing, edge-device solutions, Large Language Models (LLMs), and classical Machine Learning applications. We build custom Data Science solutions for clients across various industries, combining strong engineering practices with a research-driven mindset.

Joining Quantum means becoming part of a team that values solid technical fundamentals, continuous learning, and practical problem-solving. You'll collaborate on impactful products, work with cutting-edge technologies, and contribute to projects that turn complex ideas into real-world solutions.

Must have skills:

• 2+ years of commercial DS/ML experience
• Solid foundation in linear algebra, statistics, and probability
• Strong Python, including NumPy, Pandas, and scikit-learn
• Hands-on experience with PyTorch (or TensorFlow)
• Deep experience in at least one of: 
  • Computer Vision (modern DL: detection, segmentation, classification - ViT, YOLO, SAM); 
  • LLMs / NLP (fine-tuning, RAG, prompt engineering, embeddings, evaluation); 
  • Classical ML at scale (tabular, time series, recommender systems)
• Working knowledge of Transformers and attention; familiarity with CNNs
• Experience deploying models to production (Docker, REST/gRPC serving, basic monitoring)
• Experience with at least one cloud platform (AWS, GCP, or Azure)
• Clean code and Git workflow
• Experience with SQL
• Upper-Intermediate English (B2+) - you'll communicate directly with clients

Nice to have skills:

• Cross-domain exposure: if your main strength is CV, some LLM exposure is a plus (and vice versa)
• Edge deployment: TensorRT, OpenVINO, ONNX, quantisation, model distillation, mobile/embedded inference
• LLM tooling: LangChain/LlamaIndex, vector databases (pgvector, Pinecone, Weaviate, Qdrant), LoRA/QLoRA fine-tuning, agentic frameworks
• MLOps & model monitoring: MLflow, DVC, Weights & Biases, CI/CD for ML
• Classical CV with OpenCV (still relevant for hybrid pipelines and edge work)
• Ability to read recent papers and implement methods in new domains
• Experience working with external clients
• Participation in Kaggle competitions

Your tasks will include:

• Own full-cycle DS projects: scoping with the client, data prep, modelling, evaluation, deployment
• Build solutions across CV, LLM/NLP, and classical ML depending on the project pipeline
• Deploy models to production - cloud, edge, or hybrid, depending on client needs
• Read recent research and adapt methods to client problems
• Communicate technical decisions and trade-offs directly to clients

We offer:

• Delivering high-end software projects that address real-world problems
• Surrounding experts who are ready to move forward professionally
• Professional growth plan and team leader support
• Taking ownership of R&D and socially significant projects
• Participation in worldwide tech conferences and competitions
• Taking part in regular educational activities
• Being a part of a multicultural company with a fun and lighthearted atmosphere
• Working from anywhere with flexible working hours
• Paid vacation and sick leave days

Join Quantum and take a step toward your data-driven future.

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

About The Role

As a Senior/Lead Software Engineer in our Machine Learning department, you will take ownership of high-impact initiatives that drive product quality, monetization, and user experience. You’ll apply your expertise in Python, data analysis, and modern AI tools to build, deploy, and optimize ML solutions end-to-end. This is a hands-on technical role that blends data science and engineering to deliver measurable business outcomes. You’ll collaborate closely with cross-functional stakeholders and contribute to evolving areas such as LLMs, Generative AI, and ML infrastructure. The role offers exposure to complex data challenges and the opportunity to shape Pearl’s AI-driven capabilities.

What You’ll Do

• Build, train, and deploy ML models that improve product performance and monetization.
• Collaborate with data, product, and engineering teams across multiple internal initiatives.
• Design and implement data pipelines for extraction, transformation, and analysis.
• Apply statistical and machine learning techniques to real-world business problems.
• Work on projects involving LLMs and Generative AI technologies.
• Analyze large datasets to identify trends, insights, and optimization opportunities.
• Integrate ML models into production systems and monitor their performance.
• Communicate findings and recommendations clearly to technical and non-technical stakeholders.
• Experiment with emerging AI tools and methodologies to enhance existing workflows.
• Ensure data quality, reliability, and scalability in all deliverables.

What We’re Looking For

• 3+ years of hands-on experience in ML Engineering or Data Science.
• 5-6+ years total experience in software or data engineering.
• Strong programming skills in Python.
• Proficiency in SQL for data querying and analysis.
• Solid understanding of data processing, analysis, and visualization.
• Experience with LLMs / Generative AI tools (e.g., OpenAI, Copilot, Cursor).
• Ability to build and deploy ML models end-to-end.
• Strong analytical and problem-solving mindset.
• Experience with .NET for integration work
• Upper-intermediate English proficiency (B2 or higher).
• Familiarity with Databricks or similar data platforms (nice-to-have).
• Exposure to AWS or other cloud-based ML environments (nice-to-have).

Why Join Us?

• High-Impact Data — Work with vast datasets generated by over a million daily visits, uncovering valuable insights.
• Collaborative Analytics Team — Join a team of 30+ skilled analysts who actively share knowledge and support each other.
• Cutting-Edge Tools & Techniques — Get hands-on experience with ML, Bayesian methods, and LLMs to solve real business challenges.
• Data-Driven Culture — Thrive in an environment where data informs every decision and drives continuous improvement.

We are looking for a Data Scientist – Autonomous Systems Engineer to work on autonomous systems with a focus on computer vision, control theory, and data-driven modeling. This role is ideal for someone with strong analytical skills and experience applying data science to real-world autonomy or robotics problems.

Key Responsibilities

• Develop vision-based algorithms for perception and navigation.
• Work on data analysis and sensor fusion for multi-sensor systems.
• Build models and simulations to support system development and testing.
• Process and analyze datasets from cameras, IMUs, and other sensors to improve autonomy performance.
• Collaborate with robotics and software engineers on perception and navigation pipelines.
• Stay up to date with recent research in computer vision, autonomy, and data science.

Required Qualifications

• 2+ years of experience in data science, robotics, computer vision, or a related field.
• Knowledge of control theory, PID controllers, signal processing, and data-driven modeling.
• Understanding of geometric computer vision principles.
• Strong programming skills in Python and good working knowledge of C++.
• Experience working with Linux-based systems.
• Degree in Computer Science, Robotics, Engineering, Mathematics, or another STEM field (or equivalent practical experience).

Nice to Have

• Experience with SLAM or Visual-Inertial Odometry (VIO).
• Familiarity with OpenCV, NumPy, and ML frameworks such as PyTorch or TensorFlow.
• Experience with ROS2, Gazebo, or AirSim.
• Experience with PX4, Betaflight, or ArduPilot.
• Understanding of neural networks for computer vision.
• Interest in reinforcement learning or predictive modeling.

About AIstats

AIstats is transforming the football data market by moving from 2D to 3D, powered by a cutting-edge Computer Vision and Machine Learning ecosystem that unlocks deep insights for both fans and professionals.

What we build

Advanced Football Analytics — a mobile app for football fans an— a mobile app for football fans and bettors that reached 100k MAU in less than a year, featuring advanced statistics powered by our proprietary ML and Computer Vision technologies.

Advanced Analytics for Football Clubs — a next-generation analytics platform helping football clubs, scouts, and agents make smarter decisions both on the pitch and in the transfer market. Thanks to our early leadership in skeletal tracking data, AIstats secured several Tier-1 club partnerships within months of launching the platform.

Responsibilities

• Develop and improve statistical and machine learning models
• Analyze large-scale datasets using Python and SQL
• Conduct statistical analysis, hypothesis testing, and experiment evaluation
• Build interpretable ML solutions and explain model behavior
• Collaborate with cross-functional teams on data-driven initiatives

Requirements

• 3+ years of experience as a Data Scientist
• Strong Python skills with NumPy, Pandas, and scikit-learn
• Solid SQL knowledge; R is a plus
• Strong understanding of probability theory and mathematical statistics
• Experience with statistical testing: t-test, χ², ANOVA, Mann-Whitney, Wilcoxon, KS test, bootstrap/permutation tests, Bonferroni and FDR corrections
• Hands-on experience with XGBoost, LightGBM, and CatBoost
• Understanding of Bayesian methods
• Experience with longitudinal/panel data, mixed/fixed/random effects models, and repeated measures
• Experience with interpretable ML approaches: GAM, SHAP, partial dependence, counterfactual analysis

Nice to Have

• Experience with deep learning: Transformers, attention mechanisms, RNN/LSTM
• Knowledge of Graph Neural Networks
• Experience with Reinforcement Learning: PPO, MAPPO, MAT, multi-agent RL
• Familiarity with Google Research Football or similar environments
• Advanced Bayesian statistics: PyMC, Stan, numpyro, MCMC, hierarchical models
• Experience with causal inference: DAGs, instrumental variables, difference-in-differences
• Knowledge of probabilistic spatial models: Markov chains, HMM/DBN, MRF/CRF, Gaussian processes

What we offer

• Fully remote work format;
• Flexible start of the working day and convenient schedule;
• Stable competitive salary pegged to the USD;
• 24 days of paid vacation and 15 additional paid days off (including sick leave, corporate holidays, and national/religious holidays);
• Friendly communication culture, great product, and transparent processes;
• Dynamic work environment with a passionate team that loves sports and technology;
• Opportunities for professional growth and career development;
• No micromanagement — just trust, autonomy, and freedom to experiment.

Join our team and help drive innovation in the football industry!

Cloudfresh ⛅️ is a Global Google Cloud Premier Partner, Zendesk Premier Partner, Asana Solutions Partner, GitLab Select Partner, Hubspot Platinum Partner, Okta Activate Partner, and Microsoft Partner.

Since 2017, we’ve been specializing in the implementation, migration, integration, audit, administration, support, and training for top-tier cloud solutions. Our products focus on cutting-edge cloud computing, advanced location and mapping, seamless collaboration from anywhere, unparalleled customer service, and innovative DevSecOps.

We’re currently looking for a Data Engineer/Analyst (GCP) to join our team. In this role, you’ll design, implement, and deliver robust data platforms and analytics solutions on Google Cloud - ensuring technical excellence and client success across the full project lifecycle, from pre-sales discovery to enterprise delivery and internal projects. We’re excited to meet someone who’s ready to make a real impact.

Requirements

- Fluency in Ukrainian
- At least B2 level in English
- GCP Native Data Stack: Deep practical knowledge of BigQuery, Cloud Storage, Cloud Functions, and BigQuery ML.
- 3+ years of experience in Data Engineering
- Strong experience with Dataflow, Dataproc, Pub/Sub, Cloud Composer, or Dataform for building and maintaining optimized ETL/ELT processes in GCP.
- Proficiency in Looker / Looker Studio.
- Advanced SQL (focus on optimization and performance tuning) and Python (for API integrations and pipeline scripting).
- Comfortable in client-facing and pre-sales scenarios (live demos, requirements gathering) with the ability to translate business needs into scalable technical designs.
- A proactive, self-driven approach with high responsibility for data platform reliability and accuracy.
- Familiarity with integrating data from APIs, relational databases, NoSQL systems, and SaaS platforms.
- Ability to work seamlessly with architects, DevOps, and ML engineers to deliver end-to-end cloud solutions.

Responsibilities

- Design and build modern data platforms for enterprise clients, working with both structured and unstructured datasets at scale.
- Lead the implementation of analytics solutions ensuring strict data quality, security, and rigorous performance optimization.
- Run workshops and deliver technical presentations to stakeholders to define and refine data architectures.
- Continuously monitor and tune BigQuery cost/scalability models and ETL performance.
- Collaborate with the team during discovery phases to provide technical expertise, live demos, and solution scoping.
- Identify and explore new GCP features and agentic AI tools to automate operations and improve process analytics.

Work conditions

- Flexible Work Format: Work remotely with flexible hours, allowing you to balance your professional and personal life efficiently.
- Training with Leading Cloud Products: Access in-depth training on cutting-edge cloud solutions, enhancing your expertise and equipping you with the tools to succeed in an ever-evolving industry.
- International Collaboration: Work alongside A-players and seasoned professionals in the cloud industry.
- Expand your expertise by engaging with international markets across the EMEA and CEE regions.
- Vibrant Team Environment: Be part of an innovative, dynamic team that fosters both personal and professional growth, creating opportunities for you to advance in your career.

When applying to this position, you consent to the processing of your personal data by CLOUDFRESH for the purposes necessary to conduct the recruitment process, in accordance with Regulation (EU) 2016/679 of the European Parliament and of the Council of April 27, 2016 (GDPR).
Additionally, you agree that CLOUDFRESH may process your personal data for future recruitment processes. You can withdraw this consent at any time.

BETER is an international product group of companies operating in the B2B segment, specializing in fast sports and esports tournaments and technological solutions for their distribution.

BETER is the exclusive rights holder of tournament products, broadcasting rights, and official data, and ensures their organization through professional tournament operators, including Setka Cup and ESportsBattle, which conduct official sports and esports events in accordance with established standards and under the auspices of relevant federations and regulatory requirements.
 

We are looking for a Data Scientist who is eager to proactively identify opportunities to improve and automate our business using data science and machine learning. You will work within a small, dedicated team of data scientists collaborating closely with backend engineers, other departments, and end users, while being part of a larger ecosystem of trading and technology experts.

In this role, you will design, develop, and optimize predictive models, implement anomaly detection systems, and participate in building production-grade machine learning solutions that directly impact trading and operational processes. You’ll also get hands-on experience with (or apply your existing knowledge of) high-performance architectures, including Kafka, serverless functions, databases, CI/CD pipelines, Kubernetes, and Docker.

Responsibilities:

• Develop and refine mathematical and statistical models for predicting sports and e-sports outcomes.
• Communicate with end users, collect feedback, and build technical solutions based on it.
• Apply machine learning to improve trading strategies, automate workflows, and detect anomalies.
• Proactively identify opportunities to use data science for business optimization and process automation.
• Perform large-scale historical data analysis to generate insights and improve model performance.
• Collaborate with backend engineers to build and maintain production machine learning systems.
• Research and prototype new methods for expanding into new sports and markets.

KPIs for This Role:

• Delivery of production-ready machine learning models and pipelines for trading within agreed timelines.
• Improvement in model accuracy and reliability, measured against established benchmarks.
• Reduction of manual intervention in trading workflows through automation initiatives.

Requirements:

• 5+ years of experience in data science, analytics, or a related field.
• Proficiency in Python (pandas, numpy, scikit-learn, etc.) and working with databases.
• Strong knowledge of statistical modeling, probability, and machine learning techniques (Supervised Learning, Unsupervised Learning).
• Experience with XGBoost/LightGBM.
• Experience with large-scale data analysis and building actionable insights.
• Ability to work collaboratively in a cross-functional team and communicate results clearly.
• English level - Upper-intermediate and higher.

Nice-to-Have:

• Experience in the sports or betting industry.
• Experience with PyTorch/Tensorflow.
• Familiarity with real-time data processing (Kafka, streaming systems).
• Exposure to building data pipelines and integrating ML models into production systems.
• Knowledge of advanced ML techniques (e.g., ensemble methods, time-series forecasting, anomaly detection).

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.