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Sports Analytics Machine Learning Jobs in Manhattan, NY

Evaluate complex analytical and machine learning scenarios for technical accuracy, scalability, and business relevance. * Develop, validate, and refine statistical models, predictive analyses, and ...

This person will implement and develop machine learning models to enhance our platform ... Analyze large datasets to identify trends and patterns, and use this information to inform model ...

As a Machine Learning Engineer, you will play a critical role in shaping the future of cooking ... Strong analytical, problem-solving, and debugging skills. Excellent communication and cross ...

Machine Learning

Manhattan, NY ยท On-site

$85/hr

Title - Machine Learning ( F2F interview is required) Location - New York, NY ( Hybrid 2-3 days onsite) Rate - $85/hr Analyze large and complex datasets to derive actionable insights and inform ...

Machine Learning Engineer

New York, NY ยท On-site

$160K - $250K/yr

This also includes utilizing data science and statistical methods to analyze and optimize machine learning model performance across tasks. Lastly, this includes optimizing the aforementioned systems ...

Machine Learning Engineer

Manhattan, NY ยท On-site

$120 - $190/hr

This also includes utilizing data science and statistical methods to analyze and optimize machine learning model performance across tasks. Lastly, this includes optimizing the aforementioned systems ...

Role/Responsibilities: We are seeking a Machine Learning Engineer to join the High Frequency ... Excellent analytical skills, with strong attention to detail * Collaborative mindset with strong ...

Role/Responsibilities: We are seeking a Machine Learning Engineer to join the High Frequency ... Excellent analytical skills, with strong attention to detail * Collaborative mindset with strong ...

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Sports Analytics Machine Learning information

What is sports analytics machine learning?

Sports analytics machine learning is the application of data science and machine learning techniques to analyze sports data, such as player statistics, game outcomes, and biometric information. Professionals in this field develop models to identify patterns, predict player performance, optimize team strategies, and gain competitive advantages. This work involves collecting large datasets, cleaning and processing data, and using algorithms to extract actionable insights that can benefit teams, coaches, and athletes. Sports analytics with machine learning is increasingly used in professional sports to inform decisions about training, recruitment, and game tactics.

How do sports analytics machine learning professionals typically collaborate with coaches and athletes to impact game strategy?

Sports Analytics Machine Learning professionals often work closely with coaches and athletes by translating complex data insights into practical recommendations. They attend strategy meetings, present findings through visualizations, and help interpret trends that can influence training, player selection, and in-game tactics. Effective communication is key, as these professionals must bridge the gap between technical analyses and real-world sports applications. This collaborative environment not only enhances team performance but also provides opportunities to see the direct impact of your work on the field.

What are the key skills and qualifications needed to thrive as a sports analytics machine learning specialist, and why are they important?

To thrive as a Sports Analytics Machine Learning Specialist, you need a strong background in statistics, data analysis, programming (typically in Python or R), and an understanding of machine learning algorithms, often supported by a degree in data science, statistics, or a related field. Familiarity with data visualization tools, sports databases, and machine learning frameworks like TensorFlow or scikit-learn is essential, along with experience using SQL and data pipelines. Strong problem-solving, communication, and collaboration skills help translate complex data findings into actionable insights for coaches, players, and stakeholders. These skills are crucial for extracting meaningful patterns from vast sports datasets and driving performance improvements or strategic decisions within sports organizations.

What are popular job titles related to Sports Analytics Machine Learning jobs in Manhattan, NY?

For Sports Analytics Machine Learning jobs in Manhattan, NY, the most frequently searched job titles are:

What job categories do people searching Sports Analytics Machine Learning jobs in Manhattan, NY look for?

The top searched job categories for Sports Analytics Machine Learning jobs in Manhattan, NY are:

What cities near Manhattan, NY are hiring for Sports Analytics Machine Learning jobs?

Cities near Manhattan, NY with the most Sports Analytics Machine Learning job openings:

Infographic showing various Sports Analytics Machine Learning job openings in Manhattan, NY as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Data Scientist (Brooklyn Nets - Basketball Operations)

Brooklyn, NY โ€ข On-site

Brooklyn Sports & Entertainment
Spectator Sportsย โ€ขย 201 - 500 employees

$61K - $62K/yr

Full-time

Re-posted 29 days ago


Job description

SUMMARY

Theย Brooklyn Nets Basketball Operations department is seeking a passionate, creative, and highly analytical Data Scientist to help advance the organization's basketball analytics capabilities. This role is dedicated exclusively to supporting the Brooklyn Nets Basketball Operations team and will develop, deploy, and continuously improve predictive models, analytical frameworks, and data visualization tools that directly influence basketball decision-making across the organization.ย 

Working closely with front office executives, coaches, scouts, and fellow Basketball Analytics team members, this individual will transform complex basketball data into actionable insights that inform player evaluation, roster construction, game strategy, player development, and organizational planning. This role requires both strong machine learning expertise and a deep passion for basketball, along with the curiosity to challenge existing methodologies and introduce innovative approaches that push the organization forward.ย 

This position is part of Brooklyn Sports & Entertainment but is dedicated exclusively to the Brooklyn Nets Basketball Operations department. Unlike many roles within the organization that support multiple business units, this role works directly with the Brooklyn Nets and their Basketball Operations leadership to drive basketball strategy and decision-making.ย 

WHAT YOU WILL DO

  • Enhance and improve existing player evaluation models while developing new predictive metrics that support basketball decision-making across the Basketball Operations department.ย 
  • Design, develop, deploy, and maintain machine learning models that generate actionable insights for roster construction, player evaluation, scouting, player development, and game strategy.ย 
  • Evaluate model performance and establish monitoring frameworks to ensure predictive accuracy, reliability, and continuous improvement.ย 
  • Build intuitive and visually compelling dashboards and data visualizations that improve the accessibility and adoption of analytics products throughout Basketball Operations.ย 
  • Partner with Basketball Operations leadership, coaching staff, scouting, and front office personnel to identify analytical opportunities and translate business questions into scalable analytical solutions.ย 
  • Collaborate with members of the Basketball Analytics team to design and implement basketball software tools and research initiatives.ย 
  • Critically evaluate existing metrics and analytical methodologies while identifying opportunities to improve current models or create entirely new approaches.ย 
  • Analyze large and complex basketball datasets, including player tracking and event-level data, to uncover meaningful trends and competitive advantages.ย 
  • Document analytical methodologies, model assumptions, and technical processes to support knowledge sharing and long-term maintainability.ย 
  • Stay current with emerging developments in machine learning, artificial intelligence, basketball analytics, and sports technology to bring innovative ideas to the organization.

WHAT YOU WILL BRING

  • 3-7 years of professional experience in data science, machine learning, predictive modeling, or a related analytical field.ย 
  • Bachelor's degree or higher in Data Science, Statistics, Applied Mathematics, Computer Science, or a related quantitative discipline, or equivalent practical experience.ย 
  • Demonstrated experience developing, testing, and deploying complex machine learning models.ย 
  • Strong programming skills in Python, R, and SQL.ย 
  • Experience with modern data science libraries including Pandas, NumPy, Scikit-learn, XGBoost, PyTorch, TensorFlow, or similar frameworks.ย 
  • Experience working with large, complex datasets and production machine learning environments.ย 
  • Experience using GitHub, version control, and collaborative software development practices.ย 
  • Strong analytical thinking with exceptional attention to detail.ย 
  • Ability to communicate complex analytical concepts to both technical and non-technical audiences.ย 
  • Excellent written, verbal, and presentation skills.ย 
  • Strong curiosity, creativity, and passion for identifying new basketball metrics and analytical approaches.ย 
  • Demonstrated ability to thrive in a fast-paced, collaborative, and continuously evolving environment.ย 
  • Genuine passion for the NBA and the game of basketball.ย 

Preferred Qualificationsย 

  • Experience with Snowflake.ย 
  • Experience developing interactive analytics applications using R Shiny, Tableau, Power BI, Plotly, or similar visualization platforms.ย 
  • Experience with JavaScript visualization libraries including D3.js, Victory, Recharts, or Nivo.ย 
  • Experience applying computer vision techniques to sports analytics.ย 
  • Experience working with player tracking technologies such as Hawk-Eye or similar spatial tracking systems.ย 
  • Experience analyzing sports science, player performance, or medical datasets, including injury forecasting.ย 
  • Strong understanding of modern basketball analytics methodologies and advanced metrics.ย 
  • Experience working with cloud-based analytics platforms such as AWS, Azure, or Google Cloud Platform.ย 

WHO YOU ARE

  • Passionate about using data to improve basketball decision-making.ย 
  • Curious, innovative, and eager to challenge conventional thinking.ย 
  • Collaborative and comfortable working across multiple Basketball Operations functions.ย 
  • Self-motivated with the ability to manage multiple priorities independently.ย 
  • Detail-oriented while maintaining a strategic perspective.ย 
  • Committed to continuous learning and sharing knowledge with teammates.ย 
  • Driven by both analytical rigor and a genuine love of basketball.ย 

COMPENSATION

Salary Range: $150,000-$170,000 + Benefits

WORK ENVIRONMENT

This position is based primarily in the Brooklyn Nets Training Center located in Industry City, Brooklyn.ย 

Because this role directly supports the Brooklyn Nets Basketball Operations, the schedule will not follow a traditional Monday through Friday workweek. The successful candidate should expect to work non-conventional hours aligned with the Brooklyn Nets basketball calendar, including evenings, weekends, holidays, training camp, preseason, regular season, postseason, NBA Draft, Summer League, free agency, and other key Basketball Operations events. Flexibility and availability during critical basketball periods are essential to success in this role. ย 

This role may require regular travel in support of the Brooklyn Nets Basketball Operations department. Travel may include team road trips, training camp, Summer League, NBA Draft, scouting events, free agency, and other basketball-related activities. The frequency and duration of travel will vary throughout the year based on the team's schedule and business needs.

We are an Equal Employment Opportunity ("EEO") Employer. It has been and will continue to be a fundamental policy of the Company not to discriminate on the basis of race, color, creed, religion/creed, gender, gender identity, transgender status, pregnancy and lactation accommodations, marital status, partnership status, domestic violence victim status, sexual orientation, age, national origin, alienage, immigration, or citizenship status, veteran or military status, disability, genetic information, height and weight, arrest or conviction record, caregiver status, credit history, unemployment status, sexual and reproductive health decisions, salary history, status as a victim of domestic violence, stalking, and sex offenses, or any other characteristic prohibited by federal, state or local laws.ย