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Internship Football Data Science Jobs in Virginia

Data Scientist, Junior

Mclean, VA · On-site

$62K - $141K/yr

Join us as we use data science for good. Join us. The world can't wait. You Have: * Experience with machine learning, data mining, statistics, or graph algorithms in academic or internship ...

New

Associate Data Scientist

Arlington, VA · On-site +1

$67K - $68K/yr

... data science and machine learning techniques through professional work, internships, or research. * Experience with Python, SQL, statistical analysis, and databases. * Curiosity and a growth mindset ...

Associate Data Scientist

Arlington, VA · On-site

$67K - $68K/yr

... data science and machine learning techniques through professional work, internships, or research. * Experience with Python, SQL, statistical analysis, and databases. * Curiosity and a growth mindset ...

Yello and WayUp Top 100 Internship Programs * Computerworld Best Places to Work in IT * Newsweek ... Bachelor's Degree in Data Science, Statistics, Mathematics, Computers Science, Engineering, or ...

Showing results 21-40

Internship Football Data Science information

What is an internship football data science?

Internship Football Data Science positions are temporary roles designed for students or early-career professionals interested in applying data science techniques to football (soccer) analytics. Interns in these roles assist with collecting, processing, and analyzing football data to derive insights that can help teams with performance analysis, scouting, and strategy. Typical tasks include working with large datasets, using statistical models, and creating visualizations to inform coaching staff or management. These internships provide valuable hands-on experience and can lead to full-time opportunities in sports analytics.

What types of projects or tasks can I expect to work on during an internship in football data science?

As a Football Data Science intern, you'll typically assist with tasks like collecting, cleaning, and analyzing match or player data using tools such as Python or R. You may contribute to building statistical models to evaluate player performance or team tactics, and create data visualizations to help coaching staff make informed decisions. Collaboration is common with analysts, coaches, and sometimes software developers, offering a broad view of how data-driven insights impact real-time football decisions. This hands-on experience builds both technical and communication skills, preparing you for future roles in sports analytics.

What are the key skills and qualifications needed to thrive as an internship football data science, and why are they important?

To thrive as an Internship Football Data Science, you need a solid background in statistics, data analysis, and programming (often with a degree in mathematics, computer science, or related fields). Familiarity with technical tools such as Python, R, SQL, and data visualization platforms, as well as experience with sports analytics software, is typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you interpret complex data and present actionable insights to coaches and analysts. These competencies enable interns to contribute meaningful analysis that can inform strategies and improve team performance.

What is the difference between Internship Football Data Science vs Football Data Analyst?

AspectInternship Football Data ScienceFootball Data Analyst
Required CredentialsRelevant coursework, basic programming skillsDegree in data science, statistics, or related field
Work EnvironmentInternship setting, entry-level projectsFull-time or part-time professional role
Employer & Industry UsageSports teams, analytics startups, research projectsProfessional sports organizations, clubs, analytics firms
Search & Comparison IntentEntry-level roles, internships, learning opportunitiesCareer advancement, professional data analysis roles

Internship Football Data Science positions are entry-level opportunities focused on learning and supporting data projects in football. In contrast, Football Data Analysts are professional roles requiring more experience and specialized skills, responsible for analyzing and interpreting football data to inform decisions.

What are the most commonly searched types of Football Data Science jobs in Virginia?

The most popular types of Football Data Science jobs in Virginia are:

Summer 2027 Internship - RWE Data Scientist - Virtual

Stryker

Williamsburg, VA • On-site

$35/hr

Other

Posted yesterday

New


Stryker rating

8.2

Company rating: 8.2 out of 10

Based on 112 frontline employees who took The Breakroom Quiz

133rd of 496 rated machine equipment manufacturers


Job description

What You Get Out of the Internship

At Stryker, we believe that developing the next generation of talent is just as important as developing life-changing medical technologies. As an intern, you won’t just observe — you’ll contribute to meaningful projects, gain exposure to leaders who will mentor you, and experience a culture of innovation and teamwork that is shaping the future of healthcare. As an intern, you will:

  • Apply classroom knowledge and gain experience in a fast-paced and growing industry setting
  • Implement new ideas, be constantly challenged, and develop your skills
  • Network with key/high-level stakeholders and leaders of the business
  • Be a part of an innovative team and culture
  • Experience documenting complex processes and presenting them in a clear format

Who We Want

Challengers. People who seek out the hard projects and work to find just the right solutions.

Teammates. Partners who listen to ideas, share thoughts and work together to move the business forward.

Charismatic networkers. Relationship-savvy people who intentionally make connections with both internal partners and external contacts.

Strategic thinkers. Interns who propose innovative ideas and consistently exceed their performance objectives.

Customer-oriented achievers. Individuals with an unparalleled work ethic and customer-focused attitude who bring value to their partnerships.

Game changers. Persistent interns who will stop at nothing to live out Stryker’s mission to make healthcare better.

Opportunities Available

As a Real-World Evidence Data Science intern at Stryker, you will:

  • Work cross functionally with different departments including Clinical Affairs, Health Economics & Outcomes Research (HEOR), Regulatory Affairs, and Marketing to support real-world evidence generation programs
  • Assist in the design and execution of observational studies using claims (e.g., Premier PINC AI, NIS) and other real-world data sources
  • Support data extraction, cleaning, and analysis of structured and unstructured healthcare data, including applying NLP techniques to unstructured billing/clinical data
  • Prepare literature review summaries and evidence syntheses to support publication and regulatory submission efforts
  • Build and refine statistical models (e.g., propensity matching, survival analysis) under the mentorship of the RWE Research team
  • Shadow cross-functional team meetings to gain exposure to how RWE informs regulatory, reimbursement, and commercial strategy

What You Need

Required:

  • Currently pursuing a Master’s degree in Biostatistics, Epidemiology, Health Services Research, Health Economics and Outcomes Research (HEOR), Health/Biomedical Informatics, Data Science, or a related quantitative field; must remain enrolled in a degree-seeking program after the internship
  • Cumulative 3.0 GPA or above (verified at time of hire)
  • Must be legally authorized to work in the U.S. and not require employment-based sponsorship now or in the future
  • Proficiency in SQL and at least one statistical/analytical programming language (Python or R)
  • Coursework or applied project experience with observational/real-world data (claims, EHR, or registry data)
  • Strong written and verbal communication skills, with proven ability to collaborate and build relationships
  • Demonstrated leadership, problem-solving, and organizational skills with the ability to manage multiple priorities
  • Proficiency in Microsoft Office (Excel, Word, PowerPoint) and eagerness to learn in a dynamic environment

Preferred:

  • Prior exposure to claims databases (Medicare, MarketScan, Premier PINC AI, Optum) or EHR data structures
  • Familiarity with causal inference methods (propensity score matching, instrumental variables) and/or survival analysis
  • Experience with NLP applied to unstructured healthcare text
  • Prior coursework, thesis, or practicum work in a medtech, pharma, or payer setting

$20 min hourly wage – $35 max hourly wage, sign-on bonus, 11 paid holidays annually, and either paid corporate housing or a living stipend, dependent upon hiring location

Stryker is a global leader in medical technologies and, together with its customers, is driven to make healthcare better. The company offers innovative products and services in MedSurg, Neurotechnology, Orthopaedics and Spine that help improve patient and healthcare outcomes. Alongside its customers around the world, Stryker impacts more than 150 million patients annually.


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