Senior Analytics Engineer - Autonomy Analytics

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles ’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering all dedicated to making a real, positive impact on the driving experience for millions of people.

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

The Autonomy Analytics team is responsible for evaluating the performance of our autonomous software using data, statistics, and machine learning. Combining data from real‑world testing with our extensive simulations, our team builds the metrics and analytics that ensure our product is safe, reliable, and delights our customers.

Our team is spread geographically with some members on‑site in Pittsburgh, Palo Alto, and Dearborn. Others work fully remotely.

• Translate loosely defined questions into clear requirements, metric definitions, and analytical deliverables
• Partner closely with software development teams, test engineering, product, and analytics partners to understand needs and deliver trusted data products
• Build and maintain scalable data models in Google Big Query and similar cloud data platforms to support reporting, analysis, and operational decision‑making
• Develop dashboards and lightweight data applications in Apache Superset, Plotly Dash, or similar tools for technical and business stakeholders
• Investigate source data, identify quality issues, and implement durable fixes that improve accuracy, consistency, and reliability
• Create reusable datasets, testing practices, and documentation that strengthen trust in data and improve self‑service access
• Balance near‑term dashboard development with long‑term data modeling work to support both speed and scale
• Communicate findings, assumptions, and tradeoffs clearly to internal stakeholders and external platform or data partners as needed

• Bachelor’s degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master’s degree and 2+ years of relevant experience, or PhD)
• Experience building and maintaining analytics‑ready data models in Google Big Query or a similar cloud data warehouse
• Experience using dbt or a similar data transformation framework to develop tested, documented, and maintainable data pipelines
• Experience designing dashboards and analytical applications in Apache Superset, Tableau, or similar reporting and visualization tools
• Strong SQL skills, including complex transformations, data validation, and query optimization
• Experience with Python for data analysis and application development, including the ability to contribute to and maintain Plotly Dash dashboards
• Demonstrated ability to succeed in ambiguous environments by defining requirements, shaping metrics, and creating structure from incomplete problem statements
• Experience partnering with software development, test engineering, product, or similar cross‑functional teams to deliver measurable outcomes
• Strong foundation in data modeling, dashboard design, documentation, and quality assurance practices
• Strong written and verbal communication skills with the ability to explain analytical concepts and findings to varied audiences

• Experience supporting autonomous vehicle development or other complex hardware and software products
• Experience working with telemetry, operational, or product usage data at scale
• Experience building shared metrics and self‑service reporting solutions for engineering and product organizations
• Experience with front‑end technologies such as HTML, CSS, JavaScript, or React to support customization and enhancement of data applications and dashboards