Data Scientist – Sports Analytics and Performance Intelligence (NBA)

Reads like a ML Engineer role: putting models into production.

Location not identified

Pay: Pay not listed
Work setting: Remote — work setting source
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.
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Employment: Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

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What you’ll work on

Full posting

Develop machine learning models for player performance analysis
Analyse time series and event based sports data at scale
Engineer features from tracking, workload, and contextual datasets
Validate and monitor models in production environments
Integrate model outputs into LangChain and LangGraph workflows

From the employer’s posting

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

Integrate model outputs into LangChain and LangGraph based reasoning workflows

What you’ll bring

All qualifications

Core experience

Strong hands-on experience in data science and applied machine learning
Proficiency in Python with Pandas, NumPy and scikit-learn
Experience with time series modelling and feature engineering
Solid SQL skills for analytical querying
Experience with large scale or high frequency datasets

Qualification wording

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

Tools in this posting

Python
SQL
NumPy
pandas
scikit-learn

Source

- 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

- 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

Benefits in the posting

Full benefits wording

Comprehensive healthcare
Remote work model

From the employer’s posting.

Posting record

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Open 4 monthsWe first saw this posting 149 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records: Live
First seen by us: Jun 3, 2026 · 149 days ago
Recorded sightings: 195
Last seen by us: Oct 30, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

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Job description

View original posting ↗

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

Source details

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Pay: No pay amount identified in the saved description.
Location & working pattern: Location not supplied.
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.
More source context
- Long-term B2B contract with a stable project pipeline - Remote work model
Work authorization: No clear work-authorization passage found. Eligibility is unconfirmed.

Open source at madiffpl.zohorecruit.com ↗Read the full description ↓

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