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Data Science Sports Jobs (NOW HIRING)

With over 750 concurrent sporting fixtures at peak and more live sports streamed than anyone else ... As the Data Science Team Leader, you will be a critical part of our expanding global data ...

Masters degree in Data Analytics, Data Science, Computer Science or related technical subject area * Demonstrated experience developing models at production scale for NFL, CFB, or sports betting for ...

Data Scientist

San Francisco, CA · On-site +1

$150K/yr

Company Description Swish Analytics is a sports analytics, betting and fantasy startup building the ... This role will work at the intersection of data science, trading, and data engineering to help ...

Masters degree in Data Analytics, Data Science, Computer Science or related technical subject area * Demonstrated experience developing models at production scale for NFL, CFB, or sports betting for ...

As the leading platform for Daily Fantasy Sports, we cover a diverse range of sports leagues ... Lead and grow a high-performing team of data scientists and analysts focused on market creation and ...

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Data Science Sports information

What is a Data Science Sports?

A Data Science Sports job involves using data analytics, machine learning, and statistical models to extract insights from sports-related data. Professionals in this field analyze player performance, team strategies, injury prevention, and fan engagement to help teams, coaches, and organizations make data-driven decisions. They work with large datasets, build predictive models, and create visualizations to uncover trends and patterns. This role is essential in modern sports for optimizing performance, scouting talent, and enhancing the overall fan experience.

What does a Data Science Sports professional do?

In a Data Science Sports role, your daily tasks often involve extracting, cleaning, and analyzing large sets of sports-related data to uncover performance trends or predictive insights. You’ll likely collaborate closely with coaches, scouts, and other team members to translate your findings into strategic recommendations. Creating data visualizations, building predictive models, and presenting reports to non-technical stakeholders are also common parts of the job. This dynamic environment requires adaptability and a passion for both sports and data-driven problem solving.

What skills and qualifications are needed for a Data Science Sports position?

To thrive in Data Science Sports, you need strong analytical skills, statistical knowledge, and experience with sports data combined with a background in mathematics, statistics, or computer science. Familiarity with programming languages like Python or R, data visualization tools, machine learning platforms, and relevant sports analytics software is highly valuable. Effective communication, problem-solving abilities, and a collaborative mindset are crucial soft skills in this field. These competencies enable professionals to turn complex sports data into actionable insights that drive decision-making for teams, coaches, and organizations.

How much do data science sports make?

Data science roles in sports typically have salaries ranging from $60,000 to over $120,000 annually, depending on experience, location, and the level of responsibility. Professionals often use skills in statistics, machine learning, and data visualization tools to analyze athletic performance, team strategies, or fan engagement. Entry-level positions may start lower, while senior roles or those in major leagues tend to pay higher salaries.

What do data science sports do in sports?

Data science professionals in sports analyze large datasets to improve team performance, player health, and game strategies. They use statistical models, machine learning, and data visualization tools to identify patterns and inform decision-making in areas like player recruitment and game tactics.
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Infographic showing various Data Science Sports job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 83% Full Time, 12% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution.

Data Science Team Leader

Denver, CO • On-site

bet365
5 - 10K employees

Full-time

Re-posted 21 days ago


Bet365 rating

8.9

Company rating: 8.9 out of 10

Based on 14 frontline employees who took The Breakroom Quiz

2nd of 15 rated gambling companies


Job description

Company Description

At bet365, we're one of the world's leading online gambling companies, revolutionising the industry since 2000. Founded by Denise Coates CBE, we now employ over 9,000 people and serve over 100 million customers in 27 languages. Our focus on In-Play betting has solidified our market-leading position, offering an unmatched experience across 96 sports and 700,000 streaming events. With over 750 concurrent sporting fixtures at peak and more live sports streamed than anyone else in Europe, we handle over 6 billion HTTP requests daily and process more than 2 million bets per hour at peak.

We empower our employees to push boundaries and explore new ideas, cultivating a culture that celebrates and rewards creativity. This offers employees a wealth of opportunities for growth, giving them the opportunity to make a real impact in the world of online gambling. As a forward-thinking company, we’re breaking new ground in software innovation too, redefining what’s possible for our customers worldwide.

Job Description

This is an exceptional, hands-on, player/coach opportunity to establish, shape, and lead our Data Science capability in the United States. As the Data Science Team Leader, you will be a critical part of our expanding global data organization.

You will remain deeply technical and actively involved in writing code, building models, and executing machine learning solutions, while simultaneously mentoring and growing a high-performing team of US-based Data Scientists and Machine Learning Engineers.

We are intentionally recruiting for a specific kind of professional: someone with a startup mindset who thrives in fast-paced environments, possesses a strong bias for action, and values execution over theoretical complexity. To succeed, you must be a pragmatic problem solver who enjoys getting their hands dirty while building scalable, production-grade solutions.

Excellent stakeholder management is paramount. You will work as a key collaborative partner alongside the US Data Team Lead, Data Product Lead, and AgentOps Team Lead within the wider US Data team, while maintaining strong operational alignment and knowledge sharing with our established UK-based Data Science team.

The listed salary for this position is $155,000 -  $165,000 annually.

Qualifications
  • Proven experience working in a fast-paced, agile, or startup-like environment. You must have a demonstrated passion for “getting things done” and delivering value iteratively. 
  • Prior experience mentoring, coaching, or leading data scientists or engineers while remaining active in code development. 
  • A strong track record of designing, building, deploying, and maintaining machine learning models in production environments 
  • Superior communication skills with the ability to build strong cross-functional relationships and translate technical concepts into business outcomes for both technical and non-technical audiences. 
  • Exceptional programming skills in Python and deep expertise in data science libraries (Scikit-learn, Pandas, NumPy, XGBoost, etc.).  
  • Advanced SQL proficiency for querying and manipulating large datasets, preferably within Google BigQuery.  
  • Hands-on experience with Google Cloud Platform (GCP), ideally including the Vertex AI ecosystem (Pipelines, Workbench, Endpoints). 
  • MSc or PhD in a quantitative discipline (Computer Science, Statistics, Mathematics, Engineering) or equivalent practical industry experience. 
  • Familiarity with containerization (Docker, Kubernetes) and CI/CD principles for machine learning. 
  • Experience with real-time stream processing or event-driven architectures (e.g., Kafka). 

Additional Information
  • In this hands-on role you will devise, code, and deploy AI, machine learning and predictive models, leading by example in technical execution and code quality. This is not a pure people-management role. 
  • Building, mentoring, and guiding a pragmatic, delivery-focused team of Junior Data Scientists and Machine Learning Engineers, fostering a culture of rapid iteration, continuous learning, and software engineering discipline. 
  • Partnering closely with the Data Team Lead, Data Product Lead, and AgentOps Team Lead to align data science initiatives with product roadmaps and platform capabilities. 
  • Collaborating regularly with our UK-based Data Science team of technical excellence to share methodology, align on standards, and leverage global technical capabilities. 
  • Translating complex, ambiguous business questions into clear data science initiatives, delivering measurable business value through rapid prototyping and deployment cycles. 
  • Collaborating with Machine Learning Engineers to champion the adoption of robust MLOps practices on our Google Cloud Platform (GCP) stack, ensuring models are automated, monitored, and scalable. 
  • Establish data science workflows, standards, and code repositories from scratch in a new regional office.

bet365 provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.


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