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Professional F1 Data Analyst Jobs (NOW HIRING)

Mom's Meals

Principal Data Analyst

Ankeny, IA · Remote

F1-OPT, F1-CPT, H-1B, TN, L-1, J-1, etc. Benefits Our employees enjoy a generous package of ... Demonstrated ability to mentor junior analytics professionals * Statistical and financial analytics ...

360 IT Professionals

DATA ANALYST

Dallas, TX · On-site

Company Description 360 IT Professionals is leading name in the software development industry ... A Data Analyst with strong Analytics background to support Corporate Sales Reporting and Analytics ...

Loopback Analytics

Data Analyst

Dallas, TX · Remote

At Loopback you will enjoy success, develop your professional skills, and allow your career to ... Data visualization and interface/ manipulation development * Analytics platform enhancements and ...

Analytic Services Inc

Data Analyst

Alexandria, VA

Five (5) years of professional experience in a relevant role. * Demonstrated understanding of data ... Ability to present analytical findings in a clear, concise, and executive-level format to senior ...

Analytic Services Inc

Data Analyst

Alexandria, VA · On-site

$99K - $144K/yr

Five (5) years of professional experience in a relevant role. * Demonstrated understanding of data ... Ability to present analytical findings in a clear, concise, and executive-level format to senior ...

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Professional F1 Data Analyst information

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How much do professional f1 data analyst jobs pay per year?

As of Jul 7, 2026, the average yearly pay for professional f1 data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

How does a Professional F1 Data Analyst typically collaborate with engineers and race strategists during a race weekend?

A Professional F1 Data Analyst plays a crucial role in supporting engineers and race strategists by providing real-time data insights throughout a race weekend. They monitor car telemetry, tire performance, and competitor data to identify trends and opportunities for performance gains. Analysts work closely with the engineering team to recommend setup adjustments and inform strategists on optimal pit stop windows, helping the team make fast, data-driven decisions under pressure. Effective communication and the ability to translate complex data into actionable insights are key to successful collaboration in this fast-paced environment.

What does a Professional F1 Data Analyst do?

A Professional F1 Data Analyst collects, processes, and interprets vast amounts of data generated by Formula 1 cars during races, practice sessions, and simulations. They work closely with engineers and drivers to analyze telemetry, performance metrics, and strategy options, providing insights to improve car speed, reliability, and race outcomes. Their work involves using specialized software and statistical tools to identify trends, optimize setups, and support real-time decision-making during races. This role requires strong analytical skills, attention to detail, and a solid understanding of both motorsports and data science.

What is the difference between Professional F1 Data Analyst vs F1 Data Engineer?

AspectProfessional F1 Data AnalystF1 Data Engineer
CredentialsDegree in Data Science, Statistics, or related field; certifications in data analysis toolsDegree in Computer Engineering, Software Development, or related; certifications in data infrastructure
Work EnvironmentAnalyzing race data, creating reports, supporting team decisionsBuilding and maintaining data pipelines, managing databases and infrastructure
Industry UsageUsed across teams for performance analysis and strategyDevelops the systems that enable data collection and analysis

The Professional F1 Data Analyst focuses on interpreting data to improve race performance, while the F1 Data Engineer builds and maintains the data systems that support analysis. Both roles are essential but differ in technical scope and responsibilities.

What are the key skills and qualifications needed to thrive as a Professional F1 Data Analyst, and why are they important?

To thrive as a Professional F1 Data Analyst, you need strong analytical abilities, expertise in data science or engineering, and a solid understanding of motorsport dynamics, often supported by a relevant degree. Familiarity with telemetry analysis tools, programming languages like Python or MATLAB, and data visualization software is essential. Excellent communication, problem-solving skills, and the ability to work under pressure help analysts convey insights and collaborate effectively with race engineers and teams. These skills ensure accurate, actionable data interpretation that optimizes race strategy and car performance in a highly competitive environment.
What cities are hiring for Professional F1 Data Analyst jobs? Cities with the most Professional F1 Data Analyst job openings:
What are the most commonly searched types of F1 Data Analyst jobs? The most popular types of F1 Data Analyst jobs are:
What states have the most Professional F1 Data Analyst jobs? States with the most job openings for Professional F1 Data Analyst jobs include:
Professional F1 Data Analyst jobs near you
Principal Data Analyst

Principal Data Analyst

Mom's Meals

Ankeny, IA • Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired 1 day ago. Applications are no longer accepted.

Mom's Meals rating

6.2

Company rating: 6.2 out of 10

Based on 39 frontline employees who took The Breakroom Quiz

13th of 22 rated food delivery companies

Job description

The Principal Data Analyst is a senior, hands-on analytics leader who turns complex, crossfunctional data into clear, actionable insights that drive business outcomes as a consultative partner. This role sets the bar for analytical rigor, designs enterprisegrade BI assets, mentors analysts, and partners with business, engineering, and governance to improve decision quality and operational performance. Work emphasizes advanced analytics using Databricks, SQL, R, Power BI, Python, and the Azure data stack. 
 
Salary range: $100,003-120,000 plus 10% bonus
 
Remote hires will be required to travel to our headquarters in Ankeny, IA (company paid) on their first day for orientation.
 
At this time, we are NOT considering applicants that require immigration sponsorship (additional work authorization or permanent work authorization) now or in the future to work in the United States. This includes, but IS NOT LIMITED TO: F1-OPT, F1-CPT, H-1B, TN, L-1, J-1, etc.
 
Benefits
Our employees enjoy a generous package of benefits that we are thrilled to provide, and feel is part of what makes us different as an employer. We value our team members, and this is one way we can show it.
 
Benefits include:
-PTO, holiday pay and holiday of choice
-401(k) match
-Life insurance
-Short-term disability
-Health, dental and vision insurance
-Maternity/paternity leave
-Health savings account (HSA)
-Flex spending accounts (FSA) - health and dependent
Position Responsibilities may include, but not limited to
  • Lead highimpact analytics initiatives from problem framing through delivery; quantify value, design robust analyses, and communicate recommendations to business partners and executives
  • Partner with business leaders to identify analytics opportunities and deliver actionable insights. Present findings and recommendations to partners and executive leadership in clear, compelling formats
  • Develop analytics products and solutions using Databricks, modern Business and Artificial Intelligence tools and Agile principles
  • Implement advanced analytics where applicable, leveraging Python for advanced analytics, automation, and integration with Databricks workflows
  • Architect and publish trusted Power BI datasets and dashboards (DAX, Power Query, semantic models), establishing standards for usability and adoption
  • Build performant Databricks workflows (notebooks, jobs, SQL Warehouses) to wrangle large datasets, engineer features, and automate recurring analyses
  • Develop Python scripts for automation, data wrangling, and integration with Databricks and Azure services
  • Partner with Data Engineering on Azure data stack components (Data Factory, ADLS, Synapse/Fabric pipelines) for scalable data solutions
  • Own analysis quality: data validation, experiment/study design, sensitivity checks, and reproducibility (versioning, documentation)
  • Define and monitor KPIs; create executive scorecards and operational reporting that tie directly to business objectives
  • Coach/mentor analysts and BI developers; uplift storytelling, statistical thinking, and visualization craftsmanship across the team
  • Collaborate with Data Governance and Compliance to ensure appropriate use of PHI and adherence to privacy/security controls
  • Facilitate data stewardship and literacy across the business
  • Drive adoption of data products to scale data value
  • Stay current with emerging technologies and recommend enhancements to the analytics stack
Required Skills and Experience
  • Bachelor's degree in Data Science, Computer Science, Statistics, Economics or related field
  • 8-10+ years in analytics roles, including 3+ years leading projects
  • Proven impact delivering analytics in complex environments (multisource data, ambiguous scope) with measurable business outcomes
  • Experience operating in healthcare data environments (or demonstrated ability to quickly adapt to such contexts)
  • Demonstrated ability to mentor junior analytics professionals
  • Statistical and financial analytics expertise with deep understanding of appropriate study design and analysis techniques and business case development
  • Azure Data Stack: Data Factory, ADLS, Synapse/Fabric pipelines; familiarity with security and governance features
  • Databricks: Spark/SQL, notebooks & jobs, performance tuning, SQL Warehouses
  • SQL: Strong proficiency (ANSI/TSQL); query optimization over large, partitioned tables
  • R: Applied analytics using tidyverse/ggplot2; reproducible workflows; statistical testing and modeling fundamentals
  • Python: Data wrangling, automation, integration with Databricks and Azure services
  • Fabric and Power BI: Data modeling, DAX, Power Query (M), calculation groups, rowlevel security, deployment pipelines
  • Versioning & Reproducibility: Gitbased workflows; disciplined documentation and peer review
  • Executive storytelling: distill and translate complex analyses into clear narratives and recommended actions or analytics solutions
  • Stakeholder partnership: influence crossfunctional partners; set expectations and drive alignment
  • Demonstrated ability to deliver projects with undefined, large and/or complex scope
  • Agile delivery
  • Mentorship: develop analysts' craft (methodology, viz/design, communication)
  • Product mindset: define problem statements, success metrics, and iterate with feedback - drives adoption of analytics products and solutions
  • Ownership & judgment: operate independently, make sound tradeoffs, and uphold high quality standards
  •  
Preferred Skills and Experience
  • Master's degree in Economics, Statistics, Data Science, Computer Science or related field
  • Certifications in Databricks, Power BI, or cloud platforms (Azure preferred)
  • Experience with machine learning frameworks and MLOps practices
  • Familiarity with data governance tools and compliance standards
  • Knowledge of advanced BI features (Power BI Copilot, AI-driven analytics)
  • Familiarity with healthcare risk adjustment models such as HCC and CDPS
  • Familiarity with claims groupers such as Milliman's HCG
  • Product management training or analytics product delivery experience 
Physical Requirements
  • Repetitive motions that include the wrists, hands and/or fingers
  • Sedentary work that primarily involves sitting, remaining in a stationary position for prolonged periods
  • Visual perception to perform job including peripheral vision, depth perception, and the ability to adjust focus
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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