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How much do formula 1 internship data science jobs pay per hour?

As of Aug 3, 2026, the average hourly pay for formula 1 internship data science in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

How much do F1 data scientists make?

F1 data scientists typically earn between $70,000 and $120,000 annually, depending on experience, education, and the team they work for. Entry-level roles may start lower, while experienced professionals with advanced skills in data analysis, machine learning, and programming can earn higher salaries, often supplemented with bonuses and benefits.

Can a data scientist work in F1?

Yes, a data scientist can work in Formula 1 by analyzing race data, vehicle telemetry, and performance metrics to optimize strategies and car setups. F1 teams often seek data scientists with skills in statistical analysis, machine learning, and programming languages like Python or R, along with experience in sports analytics or engineering environments.

What is the difference between Formula 1 Internship Data Science vs Formula 1 Data Engineer Internship?

AspectFormula 1 Internship Data ScienceFormula 1 Data Engineer Internship
Required SkillsData analysis, statistical modeling, programming (Python, R)Data pipeline development, database management, programming (Python, SQL)
Work EnvironmentAnalyzing race data, predictive modeling, machine learningBuilding data infrastructure, real-time data processing
Industry UsagePerformance analysis, strategy supportData infrastructure, telemetry data handling

Both internships are within the Formula 1 industry and require programming skills. Data Science focuses on analyzing and modeling race data to improve performance, while Data Engineering emphasizes building and maintaining data systems for real-time data flow. Candidates should choose based on their technical strengths and career interests in analytics versus infrastructure development.

What types of projects can I expect to work on as a Data Science intern in Formula 1, and how do these contribute to the team's performance?

As a Data Science intern in Formula 1, you can expect to work on projects such as analyzing telemetry data, optimizing race strategies, and developing predictive models for vehicle performance. These projects often involve close collaboration with engineers, race strategists, and software developers to translate complex data into actionable insights. Your work directly supports the team’s competitive edge, as data-driven decisions can influence everything from pit stop timing to car setup. This dynamic environment provides hands-on experience with cutting-edge tools and exposes you to the fast-paced nature of motorsports analytics.

What are the key skills and qualifications needed to thrive as a Formula 1 Internship Data Science, and why are they important?

To excel in a Formula 1 Data Science Internship, you need a solid background in statistics, data analysis, and programming (such as Python or R), typically supported by current studies in mathematics, engineering, or computer science. Familiarity with data visualization tools, machine learning frameworks, and motorsport telemetry systems is highly beneficial. Strong problem-solving skills, attention to detail, and effective communication set standout candidates apart. These competencies enable interns to extract actionable insights from complex data, directly impacting race strategies and team performance.

What is a Formula 1 Internship in Data Science?

A Formula 1 Internship in Data Science is a temporary position that allows students or recent graduates to work alongside professional data scientists within a Formula 1 team or organization. Interns typically assist with data collection, analysis, and modeling to help optimize car performance and race strategy. This role provides hands-on experience with real-world motorsport data and advanced analytical tools, giving interns valuable insights into both data science and the high-paced world of Formula 1. It is an excellent opportunity for those interested in combining their passion for racing with technical skills in data analytics.

How much do F1 interns make?

F1 data science interns typically earn between $15 and $25 per hour, depending on the team and location. Internships usually last several months and may include additional benefits such as access to racing events and exposure to high-performance data analysis tools.
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Formula 1 Internship Data Science jobs near you
Infographic showing various Formula 1 Internship Data Science job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 71% Full Time, 20% Part Time, and 8% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

Data Science Internship (Data Platforms)

MHI

Lake Mary, FL • On-site

Internship

Posted 25 days ago

Job description

Data Science Associate
Company Overview
At Mitsubishi Power, we're not just building better clean energy technologies; we're architecting a better future. Our team is boldly redefining power generation to accelerate the world's energy transition. We operate as one team, pushing toward our vision of the future. We value problem solvers, prioritize collaboration, and support each other in an inclusive culture built on accountability and authenticity by demonstrating our values: Safety, Family, Innovative, Inclusive, Accountable & Courageous. Together, we're building the future we all aspire to - making net zero a reality.
Role Overview
The Data Scientist Intern supports Mitsubishi Power's IT Data Platforms team by contributing to data quality, data cataloging, and automation efforts within enterprise data environments. This hands-on internship provides practical experience working with cloud-based data platforms, centralized data repositories, and Microsoft Power Platform tools. The role collaborates with Data Platforms leadership, Enterprise Applications, and IT stakeholders to support scalable, high-quality data solutions used across the business.
Key Responsibilities
  • Assist with data quality assessments across enterprise data sources, identifying gaps, inconsistencies, and improvement opportunities.
  • Support data catalog activities including documentation of datasets, metadata, data definitions, and lineage.
  • Validate, organize, and prepare ingested data within centralized platforms such as data lakes and structured repositories.
  • Contribute to automation efforts to surface data into Microsoft Power Apps and Power Automate workflows.
  • Perform data validation and reconciliation to ensure accuracy and completeness between source and ingested data.
  • Assist with development of basic dashboards, reports, and visualizations to support data visibility and usage.
  • Support testing and user acceptance activities to validate data processes and automation solutions.
  • Maintain tracking artifacts such as data quality logs, catalog trackers, and automation inventories.
  • Document data processes, standards, and learnings to support long-term platform sustainability.

Requirements
  • Assist with data quality assessments across enterprise data sources, identifying gaps, inconsistencies, and improvement opportunities.
  • Support data catalog activities including documentation of datasets, metadata, data definitions, and lineage.
  • Validate, organize, and prepare ingested data within centralized platforms such as data lakes and structured repositories.
  • Contribute to automation efforts to surface data into Microsoft Power Apps and Power Automate workflows.
  • Perform data validation and reconciliation to ensure accuracy and completeness between source and ingested data.
  • Assist with development of basic dashboards, reports, and visualizations to support data visibility and usage.
  • Support testing and user acceptance activities to validate data processes and automation solutions.
  • Maintain tracking artifacts such as data quality logs, catalog trackers, and automation inventories.
  • Document data processes, standards, and learnings to support long-term platform sustainability.

Learning Outcomes
  • Gain hands-on experience with enterprise data platforms, including data lakes and cloud-based environments, understanding how data supports business operations.
  • Develop core data skills in data quality, validation, cataloging, and metadata management using real-world datasets.
  • Apply analytics and automation tools such as Excel, SQL, and Microsoft Power Platform to support business processes and workflows.
  • Strengthen problem-solving and communication skills by working cross-functionally and translating data insights into clear, actionable outcomes.

Mitsubishi Power is an Equal Employment Opportunity (EEO) employer actively seeking to diversify the workforce and is committed to a policy of equal employment opportunity. Therefore, all qualified applicants regardless of race, color, religion, gender, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally recognized protected basis under applicable law, are strongly encouraged to apply.

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