Senior Data Scientist

About the team365Scores 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 roleWe 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.ResponsibilitiesDesign, develop, and deploy scalable machine learning and optimization models for data-driven decision-making systemsBuild and maintain end-to-end ML pipelines, including data preparation, model training, deployment, and monitoringApply advanced machine learning, deep learning, and optimization techniques to solve complex business problemsEvaluate and improve model performance through experimentation, A/B testing, and data-driven analysisDeploy and maintain real-time ML systems operating at scaleCollaborate with cross-functional teams to translate business challenges into production-ready data science solutionsStay up to date with the latest developments in machine learning, optimization, and AIRequirements5+ years in Data Science, Machine Learning Engineering, or similar roles with proven impact in productionStrong experience with machine learning and deep learning frameworks like PyTorch or TensorFlowGood understanding of mathematical optimization (convex, constrained, gradient-based methods)Hands-on experience with Bayesian optimization and hyperparameter tuningKnowledge of causal inference methods (propensity scoring, uplift modeling, causal ML, experimentation)Experience with time-series modeling and forecastingProven experience deploying ML models in production, including real-time systemsFamiliar with MLOps practices: experiment tracking, model versioning, A/B testing, monitoringExperience building end-to-end ML pipelines from data ingestion to model servingApplying ML to decision-making systems (pricing, bidding, ranking, resource allocation) is a plusKnowledge of LLMs, reinforcement learning, or agent-based AI is an advantageStrong English (B2 or higher), written and spokenNice to haveAdvanced degree (MS/PhD) in Computer Science, Mathematics, Statistics, Engineering, or equivalent experienceContributions to open-source ML projects or researchBenefitsWork in a highly professional team with a friendly community spirit and supportive environmentWell-equipped open-space officesPaid vacation — 24 days per year, 100% sick leave paymentFlexible working hours — we care about you (!) and your output5 sick days per yearCare 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