Data Scientist – Sports Analytics and Performance Intelligence (NBA)
这是一个远程职位。我们正在寻找一个数据科学家，加入下一代的体育分析和性能智能平台支持专业篮球组织，包括 NBA 队伍。该角色重点是建立机器学习模型，将大规模的表现，跟踪和文本数据转化为教练人员，分析师，医疗团队和前台利益相关者可行的见解。该平台结合结构化和实时运动数据与机器学习和 GenAI 编排层来支持玩家评估，游戏策略，工作负载优化和伤害风险管理。它已经在现场分析工作流程中使用，并继续发展，采用更深入的数据集成和先进的推理组件。责任 ·开发机器学习模型用于玩家性能分析和优化 ·规模分析时间系列和基于事件的体育数据 ·从跟踪，工作负载和文本数据集中的工程功能 ·验证，监测和不断改进生产环境中的模型 ·与运动分析师和领域专家合作来完善分析应用案例 ·将模型输出暴露于分析仪表板和下游系统 ·将模型产出的结合到 LangChain 和 LangGraph 基于推理工作流程 ·确保模型输出可解释，可靠和准备决策的要求 · 强大的数据科学和应用机器学习经验 · 熟练掌握 Python 以及像潘达斯，NumPy 和 scikit-learn 这样的核心图书馆 ·时间系列建模和功能工程经验 ·分析查询和数据探索的 SQL 技能 · 大规模或高频率数据集的工作经验 · 在多功能产品团队工作的能力 · 具有流利的英语专业协作 · 体育分析或绩效建模经验 · 接触跟踪数据或基于事件的数据集 · 对 LangChain 和 LangGraph 进行分析调整的熟悉 ·与 GenAI 驱动的见解生成或叙事创建基础经验 • 优势 ·坚实的，竞争力的工资 · 在跨国项目中工作 ·全面医疗保健 · 与稳定的项目管道持久 B2B 合同 ·远程工作模型 原始地在喜马拉雅山上发布
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This is a remote position.
We 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.
Responsibilities
- Develop machine learning models for player performance analysis and optimisation
- Analyse time series and event based sports data at scale
- Engineer features from tracking, workload, and contextual datasets
- Validate, monitor, and continuously improve models in production environments
- Collaborate with sports analysts and domain experts to refine analytical use cases
- Expose model outputs to analytical dashboards and downstream systems
- Integrate model outputs into LangChain and LangGraph based reasoning workflows
- Ensure model outputs are interpretable, reliable, and decision ready
Requirements
- Strong hands on experience in Data Science and applied Machine Learning
- Proficiency in Python and core libraries such as Pandas, NumPy, and scikit-learn
- Experience with time series modelling and feature engineering
- Solid SQL skills for analytical querying and data exploration
- Experience working with large scale or high frequency datasets
- Ability to translate domain questions into quantitative models
- Experience working in cross functional product teams
- Fluent English for professional collaboration
Nice to have
· Experience in sports analytics or performance modelling
- Exposure to tracking data or event based datasets
- Familiarity with LangChain and LangGraph for analytical orchestration
- Basic experience with GenAI driven insight generation or narrative creation
Benefits
- Solid, competitive salary
- Work in a multinational environment on international projects
- Comprehensive healthcare
- Long-term B2B contract with a stable project pipeline
- Remote work model
Originally posted on Himalayas