Responsibilities
- Apply statistical modeling to guide data strategy for acquisition (both real and synthetic), validation, and machine learning training.
- Create metrics and frameworks to assess data distribution and diversity.
- Address ambiguous problems through data-driven analysis, delivering actionable insights to support decision-making and demonstrate business impact.
- Present findings on complex technical subjects to stakeholders across engineering leadership and product teams.
- Collaborate with engineering teams to understand their domain-specific challenges and provide data-driven recommendations.
- Promote the adoption of data science best practices across the organization and mentor other data science engineers.
Requirements
- Professional experience using Python for data science (e.g., numpy, scipy, scikit-learn, pandas) and SQL or other languages for relational databases.
- Experience with a cloud platform such as AWS, GCP, or Azure.
- Proficiency with common data science tools including statistical analysis and mathematical modeling.
- Experience developing analytical frameworks to enable data-driven decision-making under high ambiguity.
- Proven track record of building relationships with engineering and product leadership and influencing strategic business decisions.
- Ability to communicate concepts clearly and precisely to both technical and non-technical stakeholders.
- Experience working in a cross-functional environment.
Nice to Have
- Experience working in a production machine learning environment.
- Experience working with geographically distributed teams.
- Previous experience in the AD/ADAS domain or related fields such as robotics.
- Experience with temporal data or robotics sensor data.
Benefits
- Excellent health, wellness, dental, and vision coverage.
- A rewarding 401k program.
- Flexible vacation policy.
- Family planning and care benefits.
