Senior Data Scientist

About the team

365Scores is a global sports tech hub, providing tens of millions of users with real-time results, stats, news, and content across all major sports.

Our products are based on cutting-edge technologies that enable live updates and on-demand content libraries of the highest quality and scale.

About the role

We are looking for a talented and experienced Senior Data Scientist to join our data science team.

In this role, you will design, develop, and deploy advanced machine learning and optimization systems that power data-driven decision making across our products. You will collaborate closely with data engineers, analysts, product managers, and software engineers to transform complex business challenges into scalable machine learning solutions.

Your expertise in machine learning, mathematical optimization, and production ML systems will play a key role in building intelligent systems that operate in real-time and at scale.

Responsibilities

• Design, develop, and deploy scalable machine learning and optimization models for data-driven decision-making systems
• Build and maintain end-to-end ML pipelines, including data preparation, model training, deployment, and monitoring
• Apply advanced machine learning, deep learning, and optimization techniques to solve complex business problems
• Evaluate and improve model performance through experimentation, A/B testing, and data-driven analysis
• Deploy and maintain real-time ML systems operating at scale
• Collaborate with cross-functional teams to translate business challenges into production-ready data science solutions
• Stay up to date with the latest developments in machine learning, optimization, and AI

Requirements

• 5+ years in Data Science, Machine Learning Engineering, or similar roles with proven impact in production
• Strong experience with machine learning and deep learning frameworks like PyTorch or TensorFlow
• Good understanding of mathematical optimization (convex, constrained, gradient-based methods)
• Hands-on experience with Bayesian optimization and hyperparameter tuning
• Knowledge of causal inference methods (propensity scoring, uplift modeling, causal ML, experimentation)
• Experience with time-series modeling and forecasting
• Proven experience deploying ML models in production, including real-time systems
• Familiar with MLOps practices: experiment tracking, model versioning, A/B testing, monitoring
• Experience building end-to-end ML pipelines from data ingestion to model serving
• Applying ML to decision-making systems (pricing, bidding, ranking, resource allocation) is a plus
• Knowledge of LLMs, reinforcement learning, or agent-based AI is an advantage
• Strong English (B2 or higher), written and spoken

Nice to have

• Advanced degree (MS/PhD) in Computer Science, Mathematics, Statistics, Engineering, or equivalent experience
• Contributions to open-source ML projects or research

Benefits

• Work in a highly professional team with a friendly community spirit and supportive environment
• Well-equipped open-space offices
• Paid vacation — 24 days per year, 100% sick leave payment
• Flexible working hours — we care about you (!) and your output
• 5 sick days per year
• Care package: Health insurance + English classes (online)
• Partially compensated educational costs (for courses, certifications, professional events, etc.)
• Bright and memorable corporate life: corporate parties 2 times a year, gifts to employees on significant events, weekly pizza Fridays