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Vice President F1 Data Science Jobs (NOW HIRING)

Lyra Health

VP of Data and AI

$251K - $346K/yr

This leader will build and manage world-class Data Engineering, Data Science, Data Analytics, AI ... VP) managing large, diverse technical teams. * Proven experience defining and executing a ...

Lyra Health

VP of Data and AI

Charleston, WV · Remote

$251K/yr

This leader will build and manage world-class Data Engineering, Data Science, Data Analytics, AI ... As a full-time VP of Data and AI, you will be employed by Lyra Health, Inc. The anticipated annual ...

Experian

Learn more at experianplc.com The Senior Vice President, Data Science & Analytics (North America) will have holistic responsibility for all data science and analytics functions of the Financial ...

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Vice President F1 Data Science information

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$37.5K

$122.7K

$196.5K

How much do vice president f1 data science jobs pay per year?

As of Jun 11, 2026, the average yearly pay for vice president f1 data science in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What does a Vice President of F1 Data Science do?

A Vice President of F1 Data Science leads the data analytics and strategy efforts for a Formula 1 team or organization. They oversee the collection, analysis, and interpretation of massive datasets from car sensors, race simulations, and competitor analysis to inform race strategies and improve performance. This executive collaborates with engineers, strategists, and management to make data-driven decisions that can provide a competitive edge. Additionally, they are responsible for managing data science teams, setting departmental goals, and ensuring that advanced technologies like machine learning are effectively integrated into F1 operations.

What are the key skills and qualifications needed to thrive as a Vice President F1 Data Science, and why are they important?

To excel as a Vice President F1 Data Science, you need extensive expertise in data analytics, statistical modeling, machine learning, and a strong educational background in data science, mathematics, or a related field. Familiarity with advanced analytics tools (like Python, R, SQL), big data platforms, and experience with motorsport telemetry or similar high-frequency data systems are essential. Strategic leadership, strong communication, and the ability to drive cross-functional collaboration set outstanding candidates apart. These skills empower effective data-driven decision-making, optimizing team performance and maintaining a competitive edge in the fast-paced Formula 1 environment.

How does a Vice President of F1 Data Science typically collaborate with technical and non-technical teams within a racing organization?

A Vice President of F1 Data Science plays a pivotal role in bridging the gap between data scientists, engineers, and business leaders. They work closely with technical teams to set data analysis strategies, oversee model development, and ensure accurate insights drive race strategy and car performance. On the non-technical side, they translate complex data findings into actionable recommendations for management and other stakeholders, ensuring alignment with broader organizational goals. This requires excellent communication skills and the ability to foster cross-functional collaboration to maximize the team's competitive advantage.

What is the difference between Vice President F1 Data Science vs Data Science Director?

AspectVice President F1 Data ScienceData Science Director
ResponsibilitiesStrategic leadership, overseeing multiple teams, setting data science vision for F1Managing data science projects, leading teams, implementing strategies within an organization
Required CredentialsAdvanced degrees in data science, analytics, or related fields; extensive experience in F1 or motorsport analyticsMaster's or PhD in data science, statistics, or related fields; significant industry experience
Work EnvironmentExecutive-level, cross-functional collaboration, high-pressure F1 environmentTeam management, project execution, collaboration with stakeholders

The Vice President F1 Data Science focuses on strategic leadership and high-level decision-making within the F1 industry, while the Data Science Director manages day-to-day project execution and team operations. Both roles require advanced credentials and industry experience, but the VP role emphasizes vision and strategy, whereas the Director role centers on project management and technical execution.

What cities are hiring for Vice President F1 Data Science jobs? Cities with the most Vice President F1 Data Science job openings:
What are the most commonly searched types of F1 Data Science jobs? The most popular types of F1 Data Science jobs are:
What states have the most Vice President F1 Data Science jobs? States with the most job openings for Vice President F1 Data Science jobs include:
Vice President F1 Data Science jobs near you
Vice President, Data Architecture and Engineering (Remote)

Vice President, Data Architecture and Engineering (Remote)

KOHLS

Menomonee Falls, WI • On-site, Remote

$180K - $232K/yr

Other

Posted 16 days ago

Kohl's rating

5.8

Company rating: 5.8 out of 10

Based on 1,436 frontline employees who took The Breakroom Quiz

12th of 21 rated department stores

Job description

About the Role

The VP, Data Architecture and Engineering is accountable for the vision, strategy, and execution of the enterprise data platform and engineering capabilities that enable business growth, operational efficiency, and customer centric innovation. This leader partners closely with business and technology teams to elevate data into a durable and scalable enterprise asset. In alignment with the VP of A.I and Transformation, who defines enterprise A.I strategy and prioritizes business use cases, this role owns the data architecture, platforms, and engineering foundations required to operationalize, scale, and reliably run A.I solutions in production across the enterprise.

What You’ll Do

  • Define and own the data product and technical data science strategy, aligning with enterprise technology and business priorities

  • Lead the design, development, and lifecycle management of data products that support business operations, customer insights, and innovation

  • Build and scale data science capabilities, including machine learning, AI-driven solutions, and advanced analytics to optimize retail operations and customer engagement

  • Partner with business units, analytics, engineering, and product management to prioritize high-value use cases for both data products and data science applications

  • Oversee data governance, stewardship, and metadata management to ensure accuracy, compliance, and trust

  • Champion modern data and AI architectures, including cloud-native platforms, APIs, data streaming services, and real-time analytics

  • Drive data democratization, ensuring business users can easily discover, access, and leverage insights

  • Foster a product mindset and a research-to-production pipeline for data science solutions, ensuring scalability and usability

  • Manage, mentor, and grow a high-performing team of data product managers, architects, engineers, and data scientists

  • Define and monitor KPIs for both data products and data science initiatives, ensuring outcomes translate into tangible business impact

  • Represent data strategy at the executive level, influencing enterprise decisions and advocating for innovation

  • Additional tasks may be assigned

What Skills You Have

Required

  • 12+ years of experience in data leadership roles, including data product management, data platforms, and data science

  • Proven track record of building and scaling data products and machine learning/AI solutions in large, complex organizations

  • Strong expertise in modern data and AI/ML architectures, including cloud platforms (AWS, GCP, or Azure), data lakes/warehouses, and governance frameworks 

  • Exceptional executive communication and stakeholder management skills, with the ability to influence across business and technology functions

  • Demonstrated success in leading cross-functional teams spanning data science, engineering, and product management

What Kohl's employees say

Pay

Benefits

Hours and flexibility

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