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Summer Formula 1 Data Science Jobs in Raleigh, NC

Sr. Data Engineer

Raleigh, NC · On-site

$111K - $133K/yr

Develop data visualization tools to communicate insights, * Provide consulting inputs for ... CURIOSITY DRIVEN, SCIENCE FOCUSED, EMPLOYEE BUILT. Our culture is unlike any other, one where we ...

New

Sr. Data Engineer

Raleigh, NC

$111K - $133K/yr

Develop data visualization tools to communicate insights, * Provide consulting inputs for ... CURIOSITY DRIVEN, SCIENCE FOCUSED, EMPLOYEE BUILT. Our culture is unlike any other, one where we ...

New

Sr. Data Engineer

Raleigh, NC · On-site

$111K - $133K/yr

Develop data visualization tools to communicate insights, * Provide consulting inputs for ... CURIOSITY DRIVEN, SCIENCE FOCUSED, EMPLOYEE BUILT. Our culture is unlike any other, one where we ...

New

Principal Data Scientist I Are you looking to develop your Data Scientist career? Would you like to ... please contact 1-855-833-5120. Criminals may pose as recruiters asking for money or personal ...

DataStaff, Inc is seeking an AI and Data Product Director for a direct hire opportunity with one of ... Lead analytics, data science, and AI/ML initiatives supporting forecasting, optimization, decision ...

Showing results 41-60

Summer Formula 1 Data Science information

See Raleigh, NC salary details

$36.5K

$119.3K

$191K

How much do summer formula 1 data science jobs pay per year?

As of Sep 5, 2026, the average yearly pay for summer formula 1 data science in Raleigh, NC is $119,312.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,800.00 and $132,200.00 per year, depending on experience, location, and employer.

What is a Summer Formula 1 Data Science?

A Summer Formula 1 Data Science job is a seasonal internship or temporary position where you work with data related to Formula 1 racing. In this role, you analyze large sets of race data, develop predictive models, and support engineers and teams in making strategic decisions. Tasks might include optimizing car performance, evaluating race strategies, or interpreting telemetry data. It's a great opportunity for students or early-career professionals interested in both data science and motorsport to gain hands-on experience.

What are the typical projects and responsibilities for a Summer Formula 1 Data Science intern?

As a Summer Formula 1 Data Science intern, you can expect to work on projects such as analyzing race and telemetry data, developing predictive models for performance optimization, and supporting real-time decision-making during race weekends. You may collaborate closely with engineers, strategists, and other data professionals to extract actionable insights from large datasets. Daily tasks often include data cleaning, exploratory analysis, and presenting findings to both technical and non-technical team members. This role provides hands-on experience with cutting-edge analytics tools in a fast-paced, team-oriented environment.

What are the key skills and qualifications needed to thrive as a Summer Formula 1 Data Science professional?

To thrive as a Summer Formula 1 Data Science professional, you need a solid background in statistics, programming (such as Python or R), and data analysis, often supported by progress toward a relevant degree in data science, engineering, or mathematics. Experience with data visualization tools, telemetry analysis software, and familiarity with machine learning frameworks are typically required. Strong problem-solving abilities, attention to detail, and effective teamwork set top candidates apart in this role. These skills are essential for extracting actionable insights from large datasets, optimizing race strategies, and supporting performance improvements in the fast-paced F1 environment.

What is the difference between Summer Formula 1 Data Science vs Summer Motorsport Data Analyst?

AspectSummer Formula 1 Data ScienceSummer Motorsport Data Analyst
Required CredentialsDegree in Data Science, Computer Science, or related fields; knowledge of motorsport analyticsDegree in Data Analysis, Statistics, or related fields; familiarity with motorsport data
Work EnvironmentF1 teams, race weekends, high-pressure environmentMotorsport teams, event analysis, collaborative setting
Industry UsagePrimarily in Formula 1 racingBroader motorsport sectors including NASCAR, WRC, etc.
Common Search/ComparisonYesYes

While both roles involve analyzing motorsport data, Summer Formula 1 Data Science focuses specifically on F1 racing analytics, leveraging advanced data science techniques in a high-stakes environment. Summer Motorsport Data Analysts work across various motorsport disciplines, applying similar skills but with a broader industry scope.

How much do summer Formula 1 data scientists make?

Summer Formula 1 data scientists typically earn between $15 and $30 per hour, depending on experience and the team's budget. Internships or temporary roles may also include stipends or stipends plus hourly wages, often requiring skills in data analysis, programming, and familiarity with motorsport data tools.

What cities near Raleigh, NC are hiring for Summer Formula 1 Data Science jobs?

Cities near Raleigh, NC with the most Summer Formula 1 Data Science job openings:

$125K/yr

Full-time

Posted 10 days ago


Internal Revenue Service rating

7.4

Company rating: 7.4 out of 10

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Job description

WHAT IS LARGE BUSINESS AND INTERNATIONAL?

A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions
  • Position(s) are to be filled in following area(s):
    • LBI - ADCCI - Compliance Planning & Analytics (CP&A), Workload Development & Delivery (WDD). Team will be determined at time of selection.

REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:

Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the closing date of this announcement.
BASIC REQUIREMENTS (IOR) ALL GRADES:
EDUCATION: A degree that included 15 semester hours in statistics (or in mathematics and statistics, provided at least 6 semester hours were in statistics), and 9 additional semester hours in one or more of the following: physical or biological sciences, medicine, education, or engineering; or in the social sciences including demography, history, economics, social welfare, geography, international relations, social or cultural anthropology, health sociology, political science, public administration, psychology, etc. Credit toward meeting statistical course requirements should be given for courses in which 50 percent of the course content appears to be statistical methods, e.g., courses that included studies in research methods in psychology or economics such as tests and measurements or business cycles, or courses in methods of processing mass statistical data such as tabulating methods or electronic data processing.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: Combination of education and experience includes courses as shown in A above, plus appropriate experience or additional education. The experience should have included a full range of professional statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying statistical techniques such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
SPECIALIZED EXPERIENCE GS-14: In addition to meeting basic requirements, to be eligible for this position at this grade level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service.
Specialized experience for this position includes:

  • Experience identifying and assessing the validity and reliability of relevant data sources and retrieving structured and unstructured data in multiple types and formats, including Extensible Markup Language (XML) files and large datasets, for use in data science projects.
  • Experience cleaning, transforming, combining, and integrating structured and unstructured data from multiple sources, including identifying and resolving missing values, outliers, and duplicate records, to prepare data for analysis.
  • Experience applying data-mining process models, including the Cross-Industry Standard Process for Data Mining (CRISP-DM) or Sample, Explore, Modify, Model, Assess (SEMMA), to collect, prepare, analyze, and evaluate data during data science projects.
  • Experience applying statistical methods, probability, statistical inference, hypothesis testing, experimental design, forecasting, and sampling methods to analyze data, evaluate results, and support program or business decisions.
  • Experience developing and evaluating analytical and artificial intelligence models using machine learning, text analytics, natural language processing, large language models, graph theory, link analysis, optimization models, complex adaptive systems, or deep-learning neural networks.
  • Experience using programming languages, query languages, data-intelligence platforms, and data-storage technologies, including R, Python, Structured Query Language (SQL), Java, Databricks, Sybase, Oracle, or open-source databases, to retrieve, process, query, analyze, and integrate data during data science projects.
  • Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing technical deliverables for validity and reliability; and communicating analytical findings, model results, limitations, conclusions, and recommendations to technical and nontechnical stakeholders through written products, presentations, graphs, tables, charts, or business-intelligence products.


AND
You must also meet the following requirement(s):

  • TIME AFTER COMPETITIVE APPOINTMENT (TACA): By the closing date (or if this is an open continuous announcement, by the cut-off date) specified in this job announcement, current civilian employees must have completed at least 90 days of federal civilian service since their latest non-temporary appointment from a competitive referral certificate, known as time after competitive appointment. For this requirement, a competitive appointment is one where you applied to and were appointed from an announcement open to "All US Citizens"
  • TIME IN GRADE (TIG): For positions above the GS-05,applicants must meet applicable time-in-grade requirements to be considered eligible. One year (52 weeks) at the next lower grade level is required to meet the time-in-grade requirements for the grade you are applying for. For positions at the GS-05, you cannot advance to the GS-05 if you have held a GS-02 in the past 52 weeks. There is no TIG restriction for GS-02, 03 or 04 positions.


For more information on qualifications please refer to OPM's Qualifications Standards.

Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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