Director of Data Science

Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options. The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, verifying and validating the autonomy stack, and defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis. Mission Summary: As the Director of Data Science, you will lead the strategic vision and execution for extracting intelligence from petabyte-scale on-road fleet data and simulation ecosystems. This leadership role is centered on building advanced data-driven methodologies, developing predictive and generative models, and serving as the primary analytical anchor supporting not only the Systems Readiness and Performance/Metrics teams but the whole company. You will drive the statistical rigor necessary to translate raw road data into high-fidelity performance metrics that directly inform vehicle launch readiness and safety-critical decisions. What You'll Be Doing: - Rapid Operational Analytics: Execute fast-turnaround investigations on emergent fleet issues, converting real-time operational data into high-impact insights for launch decisions. - Advanced Exposure Modeling: Build complex statistical models to evaluate vehicle safety and performance across diverse environmental variables and Operational Design Domains. - Cross-Functional Partnership: Serve as the primary analytical anchor for Systems and Autonomy teams (Perception, Prediction, Planning).

- Executive Artifacts: Work with other systems teams to distill raw telemetry and rapid-response findings into high-level strategy documents, visualizations, and dashboards. - Team Leadership: Mentor and scale a dedicated four-person team, instilling a culture that pairs rapid analytical agility with absolute scientific rigor. What We're Looking For: - Industry Experience: 10+ years of professional experience leading data science or applied AI/ML initiatives, with at least 5 years explicitly scaling data-driven programs for autonomous driving, robotics, or complex safety-critical engineering systems. - Educational Background: Master’s degree or PhD in Data Science, Computer Science, Robotics, Mathematics, Physics, or a highly quantitative field. - Expertise in Advanced Analytics: Deep foundational knowledge in statistical analysis, density estimation, hypothesis testing, uncertainty quantification, and causal reasoning. - Technical Proficiency: Mastery of Python, SQL, and data science infrastructure libraries, alongside a strong understanding of modern sequence modeling (Transformers) and distributed compute scaling frameworks (e. g. , Ray, AWS). - System Deconstruction: Demonstrated track record of translating ill-defined, ambiguous real-world performance questions into structured metric designs and concrete solution architectures. - Exceptional Communication: Proven capacity to articulate highly technical data patterns and trade-offs into compelling strategies for cross-functional engineering peers and C-suite executives. - Collaborative Leadership: Strong interpersonal ability to wield cross-functional technical influence, resolve technical disagreements across teams, and establish organizational best practices around data integrity. Bonus Points (not required): - Experience designing reward functions or applying Inverse Reinforcement Learning (IRL) to evaluate human-like driving intent, assertiveness, and comfort.