Toyota's R&D Division is looking for a Data Analytics Engineer specializing in vehicle data evaluation to lead the analysis and interpretation of vehicle data to drive innovation and improve vehicle performance.
Requirements
- 5+ years of experience in data analytics or engineering roles, with at least 2 years focused on vehicle or IoT data.
- 3+ years using SQL and Python (including data manipulation and statistical analysis libraries such as Pandas, NumPy, and SciPy).
- 3+ years building and maintaining data pipelines using tools like Airflow, dbt, Spark, or similar.
- 3+ years working with vehicle data ecosystems: CAN bus, OBD-II, telematics, GPS, IMUs, and related protocols.
- 3+ years working with cloud-native data stacks (AWS/GCP/Azure) and modern data warehousing (e.g., BigQuery, Snowflake
- 3+ years experience translating complex vehicle and engineering concepts into actionable data insights for both technical and non-technical audiences.
- 3+ years experience in electric or autonomous vehicle systems, advanced driver-assistance systems (ADAS), or vehicle control systems.
Responsibilities
- Lead the design and optimization of robust, scalable data pipelines for ingesting and analyzing vehicle telemetry, diagnostics, and sensor data at scale.
- Serve as a technical authority in vehicle data analytics, guiding data strategy and influencing product and engineering roadmaps.
- Develop high-impact dashboards, models, and tools to derive actionable insights from vehicle performance and usage data.
- Mentor junior engineers and analysts, promoting best practices in data quality, governance, and engineering.
- Partner closely with stakeholders across R&D, product, embedded systems, and operations to frame complex business and engineering challenges as data problems.
- Drive initiatives involving advanced analytics, predictive modeling, and anomaly detection to support vehicle reliability, safety, and operational efficiency.
- Own the full data lifecycle from ingestion through visualization, ensuring reliability, scalability, and performance.
Other
- Bachelor’s or Master’s degree in Computer Science, Data Science, Electrical/Mechanical Engineering, or a related field.
- Willingness to travel both domestically and internationally, up to 10% of the time.
- Willingness to work overtime up to 20% of the time.
- Leadership in cross-functional project planning, technical architecture reviews, or data governance initiatives.
