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Freelance 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 ...

Data Science Team Leader

Denver, CO · On-site

$155K - $165K/yr

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 ...

Data Science Team Leader

Denver, CO · On-site

$155K - $165K/yr

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 ...

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 ...

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

The dietitian will use clinical expertise, sports nutrition science, and objective player data to create practical, player-centered solutions that support both short-term performance and long-term ...

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Freelance Data Science Sports information

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$14

$47

$132

How much do freelance data science sports jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for freelance data science sports in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.

What are some common challenges freelance data scientists face when working on sports analytics projects?

Freelance data scientists in the sports industry often encounter challenges like accessing high-quality, up-to-date datasets, as sports organizations may have strict data privacy policies. Additionally, communicating complex analytical findings to non-technical stakeholders, such as coaches or athletes, requires strong visualization and storytelling skills. Freelancers must also effectively manage their time and deliverables, as project scopes and timelines can change rapidly depending on client needs and sporting seasons.

What is a freelance data science sports professional?

A Freelance Data Science Sports professional is an independent contractor who uses data science techniques, such as statistical analysis, machine learning, and data visualization, to analyze and interpret sports data. They work with sports organizations, teams, media companies, or betting agencies to help improve performance, make predictions, or extract insights from game statistics. Their projects can range from player performance analysis to developing predictive models for game outcomes. Freelance professionals typically manage their own workloads and clients, offering flexibility and specialized expertise.

What are the key skills and qualifications needed to thrive as a freelance data science sports professional?

To thrive as a Freelance Data Science Sports professional, you need solid statistical analysis skills, proficiency in data manipulation, and a strong understanding of sports analytics, typically supported by a degree in statistics, mathematics, or computer science. Mastery of tools such as Python or R, data visualization platforms, and experience with sports data APIs are highly valuable. Strong communication, problem-solving, and self-management skills help you effectively interpret data insights and manage client relationships. These skills are crucial for delivering actionable insights and maintaining client satisfaction in a dynamic, results-driven industry.

What is the difference between Freelance Data Science Sports vs Freelance Data Analysis Sports?

AspectFreelance Data Science SportsFreelance Data Analysis Sports
Required SkillsAdvanced statistical analysis, machine learning, programming (Python, R)Data cleaning, basic statistical analysis, reporting
Work EnvironmentProject-based, remote or on-site, collaboration with sports teams or companiesRemote or freelance projects, often with sports organizations or media
Industry UsageDeveloping predictive models, athlete performance analysis, sports analytics platformsGenerating reports, analyzing game data, providing insights

Freelance Data Science Sports involves advanced analytics, machine learning, and predictive modeling, often requiring programming skills. Freelance Data Analysis Sports focuses on interpreting data, creating reports, and providing insights with less emphasis on complex algorithms. Both roles serve the sports industry but differ in technical depth and scope.

More about Freelance Data Science Sports jobs
What cities are hiring for Freelance Data Science Sports jobs? Cities with the most Freelance Data Science Sports job openings:
What are the most commonly searched types of Data Science Sports jobs? The most popular types of Data Science Sports jobs are:
What states have the most Freelance Data Science Sports jobs? States with the most job openings for Freelance Data Science Sports jobs include:
Infographic showing various Freelance Data Science Sports job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $99,230 per year, or $47.7 per hour.

Data Science Team Leader

bet365

Denver, CO

Full-time

Re-posted 21 days ago


Bet365 rating

9.2

Company rating: 9.2 out of 10

Based on 13 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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