2027届-数据分析实习生，车辆固件-上海

What To Expect Vehicle Firmware is where code meets physics. Millions of Tesla vehicles generate rich telemetry from chassis, drive, and thermal systems daily — data that reveals how our vehicles actually perform in the real world.

You'll work with firmware engineers, dive into vehicle telemetry, and uncover insights that directly influence brake control, motor optimization, and thermal management. Your work will help ship firmware that makes vehicles safer, more efficient, and more reliable.

What You'll Do

• Answer firmware and vehicle behavior questions using telemetry, alerts, and logs — transforming raw data into actionable findings
• Navigate incomplete or conflicting data to deliver concise conclusions: what happened, confidence level, and next steps
• Partner with chassis, drive, and thermal engineers to define signals, time windows, and statistical approaches
• Use AI agents by default, verifying outputs against physics and the data
• Present findings in clear technical language

What You'll Bring Must Have

• Expected start date: September 2026 or early October 2026
• Availability: Minimum 4 months full-time, 5 days/week on-site in Shanghai; 6 months or above preferred
• Engineering sense — Vehicle systems, mechanical, electrical, controls, or related fields. You reason about how the vehicle behaves, not just how to query a table
• Critical thinking — You question metrics and obvious plots before concluding. Correlation isn't causation
• Comfort with messy data — logs, sensors, experiments, field data. You find signal in noise. SQL is useful, not the bar
• Fast learner — Quick to ramp up on internal systems and vehicle context
• AI-native — You use AI agents to move faster and verify their outputs rigorously
• Python proficiency — pandas, Jupyter, plots or similar

Plus

• Vehicle dynamics, firmware, CAN bus, or controls coursework/projects

What This Role Is (and Isn't)

• For you if: You want to be embedded with firmware engineers, doing analysis that influences product decisions. You care more about insight than infrastructure.
• Not for you if: You're primarily interested in building production data pipelines, Spark/Airflow workflows, or Docker/Kubernetes services.
• Opportunity to convert to full-time: Possible with outstanding performance and passing the evaluation interview.