{"id":2170148,"url":"https://alion.io/job/madiff-data-scientist-sports-analytics-and-performance-intelligence-nba","title":"Data Scientist – Sports Analytics and Performance Intelligence (NBA)","company":{"id":4374669,"name":"Madiff","domain":"madiff.eu","url":"https://alion.io/company/madiff-2","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Zoho Recruit","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"unspecified","remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false}],"status":"live","first_seen_at":"2026-10-09T11:43:20Z","employer_posted_date":"2026-10-21","last_verified_at":"2026-10-27T00:59:10Z","board_verified":true,"closed_at":null,"days_open":17,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":17},"description":"This is a remote position.\nWe are looking for a Data Scientist to join a next generation sports analytics and performance intelligence platform supporting professional basketball organisations, including NBA teams. The role focuses on building machine learning models that transform large scale performance, tracking, and contextual data into actionable insights for coaching staff, analysts, medical teams, and front office stakeholders. The platform combines structured and real time sports data with machine learning and GenAI orchestration layers to support player evaluation, game strategy, workload optimisation, and injury risk management. It is already used in live analytical workflows and continues to evolve with deeper data integration and advanced reasoning components.\nResponsibilities\nDevelop machine learning models for player performance analysis and optimisation\nAnalyse time series and event based sports data at scale\nEngineer features from tracking, workload, and contextual datasets\nValidate, monitor, and continuously improve models in production environments\nCollaborate with sports analysts and domain experts to refine analytical use cases\nExpose model outputs to analytical dashboards and downstream systems\nIntegrate model outputs into LangChain and LangGraph based reasoning workflows\nEnsure model outputs are interpretable, reliable, and decision ready\nRequirements\nStrong hands on experience in Data Science and applied Machine Learning\nProficiency in Python and core libraries such as Pandas, NumPy, and scikit-learn\nExperience with time series modelling and feature engineering\nSolid SQL skills for analytical querying and data exploration\nExperience working with large scale or high frequency datasets\nAbility to translate domain questions into quantitative models\nExperience working in cross functional product teams\nFluent English for professional collaboration\nNice to have\nExperience in sports analytics or performance modelling\nExposure to tracking data or event based datasets\nFamiliarity with LangChain and LangGraph for analytical orchestration\nBasic experience with GenAI driven insight generation or narrative creation\nBenefits\nSolid, competitive salary\nWork in a multinational environment on international projects\nComprehensive healthcare\nLong-term B2B contract with a stable project pipeline\nRemote work 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