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F1 Data Science Jobs in Washington, DC (NOW HIRING)

ECS

AI Model Engineer

Ashburn, VA · On-site

$125K - $150K/yr

Utilize multimodal architectures for robust retrieval and data fusion. * Coordinate the planning ... Minimum Bachelor's degree in Computer Science, Electrical Engineering, or a related technical field ...

Umd

IT Engineer, Workday Integrations

College Park, MD · On-site

$116K - $140K/yr

Master's degree in Computer Science, Software Engineering, or related technical field Technical ... F1 STEM OPT support is not available for this position. Required Application Materials: Resume ...

Federated Wireless Inc.

Product Manager

Arlington, VA · On-site

$120K - $150K/yr

Analyze customer feedback, product usage data, market trends, and competitive dynamics to identify ... Bachelor's degree in Business, Engineering, Computer Science, Economics, or related field * 3-6 ...

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All JobsF1 Data Science JobsF1 Data Science Jobs in Washington, DC

F1 Data Science information

See Washington, DC salary details

$42.5K

$139K

$222.6K

How much do f1 data science jobs pay per year?

As of Sep 8, 2026, the average yearly pay for f1 data science in Washington, DC is $139,013.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,600.00 and $154,000.00 per year, depending on experience, location, and employer.

What is an F1 Data Science?

An F1 Data Science job involves analyzing vast amounts of racing data to optimize car performance, race strategy, and driver decision-making. Data scientists in Formula 1 work with telemetry, simulations, and real-time data to extract insights that improve speed, reliability, and efficiency. They use machine learning, statistical modeling, and engineering principles to enhance car aerodynamics, tire management, and fuel strategy. This role requires a strong background in data analytics, programming (Python, MATLAB, SQL), and a deep understanding of motorsport dynamics.

What does an F1 Data Science do?

As an F1 Data Science professional, your daily tasks typically include analyzing real-time and historical race data to inform car performance optimization and race strategies. You’ll work closely with engineers, strategists, and drivers to interpret data from sensors and telemetry, build predictive models, and communicate findings to support decision-making. The role often involves developing and maintaining data processing pipelines as well as creating informative visualizations for both technical and non-technical stakeholders. Collaboration is key, as you’ll be part of a multidisciplinary team working together under tight deadlines during race events and testing sessions. This dynamic environment offers exciting opportunities to directly impact race outcomes through your data-driven insights.

What skills and qualifications are needed for an F1 Data Science?

To thrive in an F1 Data Science role, you need a strong background in statistics, data analysis, programming (e.g., Python, R), and a solid understanding of motorsport engineering concepts, typically supported by a relevant degree in data science, engineering, or physics. Proficiency in data visualization tools, machine learning libraries, and race telemetry analysis systems is highly valued. Strong problem-solving ability, attention to detail, and clear communication are essential soft skills, as is a collaborative mindset for working closely with engineers and race strategists. These abilities are important for extracting actionable insights from complex data, optimizing car and team performance, and delivering results in the high-pressure, fast-paced environment of Formula 1.

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 car setup and strategy. F1 teams often seek data scientists skilled in statistical analysis, programming, and tools like Python, R, and SQL to support decision-making and performance improvements.

What are the most commonly searched types of F1 Data Science jobs in Washington, DC?

The most popular types of F1 Data Science jobs in Washington, DC are:

What are popular job titles related to F1 Data Science jobs in Washington, DC?

For F1 Data Science jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching F1 Data Science jobs in Washington, DC look for?

The top searched job categories for F1 Data Science jobs in Washington, DC are:

F1 Data Science jobs near you
Infographic showing various F1 Data Science job openings in Washington, DC as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 80% Physical, 4% Hybrid, and 16% Remote job distribution, with an average salary of $139,013 per year, or $66.8 per hour.

AI Model Engineer

ECS

Ashburn, VA • On-site

$125K - $150K/yr

Full-time

Posted 7 days ago

Job description

Everforth ECS is seeking an AI Model Engineer to work in a hybrid remote/onsite capacity, with minimum of 3 business days onsite at our Fairfax, VA corporate office and/or our Ashburn, VA customer site.
Please note: This position is contingent upon contract award
Everforth ECS is seeking an accomplished AI/ML Engineer to provide technical leadership and strategic guidance on the integration of advanced artificial intelligence and machine learning solutions to support mission-critical government and defense objectives. The ideal candidate is innovative with a track record of evaluating, experimenting with, and transitioning emerging technologies into operational use. This role requires exceptional communication skills, strong technical expertise, and experience collaborating across the Department of Homeland Security (DHS) and other government agencies. The AI Engineer will design, train, implement, and maintain end-to-end machine learning algorithms and their pipelines, automating deployment and monitoring processes while ensuring performance, observability, and security. This role contributes to building scalable infrastructure, real-time dashboards, and automated pipelines that enable secure, compliant, and efficient AI operations aligned with mission and business goals.
Key responsibilities include:
  • Design, build, train, and fine tune computer vision models for object detection, tracking, and classification tasks.
  • Utilize multimodal architectures for robust retrieval and data fusion.
  • Coordinate the planning, development, and execution of cutting-edge research programs designed to experimentally validate novel AI/ML concepts.
  • Evaluate emerging technologies from academia and industry for their potential impact on national security.
  • Serve as a subject matter expert, providing technical leadership and strategic recommendations to government decision-makers on AI/ML technology, adoption, and implementation.
  • Set the technical direction for advanced computer vision and AI capabilities supporting exploitation of remote sensing data, including EO and hyperspectral imagery.
  • Conduct rapid feasibility studies and prototype implementations to evaluate emerging algorithms, model architectures, and data exploitation approaches.
  • Use prototype-driven demonstrations and technical studies to shape applied research programs and support proposal development for new AI initiatives.
  • Advance the application of vision-language and multimodal foundation models for analysis, retrieval, and reasoning over large-scale EO/IR and hyperspectral datasets.
  • Work closely with mission partners to refine problem definitions, evaluate prototype systems, and ensure developed capabilities transition rapidly into operational environments.
  • Prepare and deliver high-quality technical briefings, documentation, and presentations for both technical and non-technical audiences
  • Utilizing data pipelines in Databricks, Apache Spark, and related ETL technologies (e.g., AWS Glue, Apache Airflow).
  • Ensuring compliance with DHS security and accreditation standards, including STIGs and Impact Level controls.
  • Providing architectural oversight on data ingestion, curation, and storage to produce reliable, high-quality datasets for AI/ML development.
  • Supporting DevSecOps practices, CI/CD pipelines, and automation to streamline delivery.

Note: Candidates must be able to clear and maintain a Public Trust Clearance from the US federal gvmt. This requires US Citizenship and the ability to pass an in-depth background check.
Salary Range: $125,000-$150,000
General Description of Benefits
  • Must be a US Citizen with the ability to obtain and maintain a Public Trust determination
  • Minimum Bachelor's degree in Computer Science, Electrical Engineering, or a related technical field
  • 6+ years of experience in software engineering and data engineering
  • Experience with cloud architecture
  • Proficiency with AI/ML frameworks (e.g., TensorFlow, PyTorch, YOLO, ONNX)
  • Proficiency in Linux -- system administration, scripting in Bash, troubleshooting
  • Strong foundation in AI/ML algorithms and ability to implement agentic workflow, and prompt engineering
  • Experience in large language model (LLM) applications
  • Strong understanding of model evaluation metrics (e.g., precision, recall, F1) and statistical drift detection methods
  • Expertise in containerization and orchestration (Docker, Kubernetes, OpenShift) and CI/CD automation (GitHub Actions, Jenkins)
  • Proficiency in building and managing ETL pipelines (e.g. AWS Glue, Apache Airflow)
  • Strong communication skills with the ability to interface and collaborate with project managers, stakeholders, vendors, and technical staff

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