Senior Data Scientist at 365Scores
On The Spot Development
This role is a production-focused Data Scientist position at 365Scores, a global sports tech platform. You will design, develop, and deploy machine learning and optimization models that drive real-time, data-driven decisions across sports content and user engagement. You'll work end-to-end from data pipelines to serving models in production, collaborating with data engineers, product managers, and software engineers. The core is building scalable ML systems for tasks like pricing, ranking, and recommendation, with heavy emphasis on MLOps, experimentation, and real-time inference.
Brak jawnych widełek — wynagrodzenie do ustalenia podczas rekrutacji.
Brakuje: workplace type (remote/hybrid/office) not specified, salary range not provided.
This role is a production-focused Data Scientist position at 365Scores, a global sports tech platform. You will design, develop, and deploy machine learning and optimization models that drive real-time, data-driven decisions across sports content and user engagement. You'll work end-to-end from data pipelines to serving models in production, collaborating with data engineers, product managers, and software engineers. The core is building scalable ML systems for tasks like pricing, ranking, and recommendation, with heavy emphasis on MLOps, experimentation, and real-time inference.
- ✓Real product at scale: tens of millions of users, real-time sports data
- ✓Opportunity to work on cutting-edge ML systems (real-time inference, optimization)
- ✓Paid vacation: 20 business days per year
- ✓100% sick leave payment
- ✓Equipment provided
- ✓Legal and accounting support in Poland (valuable for foreign workers)
- ✓English and Polish classes offered
- ✓Informal and friendly atmosphere mentioned
- −Outsourcing model: employment is via On The Spot Development, not directly at 365Scores, which may affect team integration and long-term career growth
- −Unclear contract type: listed as 'other' without further specification
- −5 sick days per year is low compared to typical Polish labor standards (33 days at half pay after 30 days)
- !No information on salary range
- !No mention of remote work policy; office in Warsaw is mentioned but not required days
- !Benefits like 'partially compensated educational costs' are vague
- !No details on team size or reporting structure
- !Medical insurance only after probation period
- ?Brak jawnych widełek — wynagrodzenie do ustalenia podczas rekrutacji
- •Design and deploy machine learning and optimization models for real-time decision-making
- •Build end-to-end ML pipelines: data preparation, training, deployment, monitoring
- •Conduct A/B testing and causal inference experiments to evaluate model impact
- •Apply deep learning (PyTorch/TensorFlow) and Bayesian optimization to solve business problems
- •Develop time-series forecasting models for sports data (e.g., scores, trends)
- •Collaborate with cross-functional teams to translate business requirements into ML solutions
- •Maintain and improve real-time ML systems serving millions of users
- •Stay current with ML research and integrate new techniques (e.g., LLMs, reinforcement learning)
Oferta dla doświadczonych specjalistów (Senior).
A data scientist or ML engineer with at least 5 years of experience, proficient in PyTorch/TensorFlow, and with hands-on production deployment experience, including real-time systems. Basic knowledge of optimization and causal inference is expected.
This role is not suitable for junior or mid-level data scientists without production ML experience. Candidates with less than 5 years of relevant experience or lacking real-time deployment skills will likely be underqualified.
- ?What is the specific contract type (other) – is it B2B or something else?
- ?Is the role remote, hybrid, or fully office-based? If hybrid, how many days per week in Warsaw?
- ?What is the size of the data science team and who will I work most closely with?
- ?Can you describe a typical project or example of a model deployed recently?
- ?What is the budget for educational courses and conferences?
- ?Are there on-call responsibilities or production support duties for ML systems?
- ?What is the tech stack beyond PyTorch/TensorFlow (e.g., cloud, ML platform, databases)?
- ?How is the probation period structured and what are performance evaluation criteria?
- −Workplace type (remote/hybrid/office) not specified
- −Salary range not provided
- −Team size and structure
- −Tech stack details (cloud, infrastructure, ML platform tools)
- −On-call or production support expectations
- −Recruitment process overview
- −Probation period length and details
Informal and friendly atmosphere with a professional approach; team is part of a global sports tech hub.