Senior Data Scientist Verification & Validation

(Senior) Data Scientist (all genders) - Verification & Validation

Hamburg, Germany

As the Verification & Validation team, we ensure that autonomous driving systems are safe, reliable, and ready for the road. We bridge simulation, testing, and real-world validation through data-driven insights and visual models. Our mission is to answer the critical question: "Is the system ready to deploy?"

We're a diverse group with backgrounds in data science, machine learning, statistics, and automotive testing. We value collaboration, curiosity, and the drive to solve complex problems that directly impact road safety.

Be a data scientist!

Develop Computer Visionand statistical models for vehicle behavior validation, scenario analysis, and test coverage assessment.

Create models for anomaly detection, scenario classification, and validation of digital twins (vehicle models, sensor models, 3D environments).

Design and implement data pipelines to process large-scale test data from simulation ( SiL , HiL ) and vehicle testing.

You build it, you run it. With the help of AI Engineers and support from platform teams, you take full ownership over your model code from testing to maintenance and deployment.

Analyze multi-modal sensor data (camera, lidar, radar, GPS ) and system logs to identify patterns, trends, and outliers.

Be an analyst!

Validate simulation fidelity against real-world vehicle data through statistical analysis.

Develop dashboards and visualizations that communicate complex test results to stakeholders.

Support root cause analysis for test failures and system anomalies.

Build metrics to assess scenario realism and representativeness across testing platforms.

Contribute to homologation and regulatory compliance through data analysis and reporting.

Be a team player!

Collaborate closely with V&V engineers, function developers, and simulation teams to translate requirements into analytical solutions.

Support cross-functional teams with data-driven insights for test strategy optimization.

Share knowledge through documentation, presentations, and pair programming sessions.

Contribute to continuous improvement of V&V processes and methodologies.

You have a background in data science, machine learning, statistics, or a related technical field.

You're proficient in Python and SQL
, and comfortable building data pipelines and analysis scripts. Experience with statistical modeling (regression, classification, clustering, anomaly detection) and time-series analysis is essential.

Previous experience with professional software engineering practices
, like version control (git), unit testing, and an understanding of the python package ecosystem.

You have experience with data visualization tools (e.g., Apache Superset, Tableau, or custom solutions) and know how to tell compelling stories with data.

You're familiar with cloud platforms (AWS, GCP, or Azure) and understand how to build scalable analytics solutions. Bonus points if you've worked with data warehouses like Redshift or Snowflake.

You have a collaborative mindset and can translate complex analytics into actionable insights for diverse stakeholders—from engineers to decision-makers.

You're curious and analytical
, with an investigative approach to problem-solving. You don't just find patterns—you understand what they mean and why they matter.

Nice to have:

Understanding of autonomous driving systems, V&V processes, or automotive KPIs ( MTBI , roadmanship).

Experience with simulation platforms ( VTD , Unity, Unreal, Carla) or automotive data formats (mcap, mf4, ROS bags).

Knowledge of safety standards (ISO 26262, ASPICE ) or EU regulations for autonomous vehicles.

Familiarity with ML deployment (MLOps) and workflow orchestration (Apache Airflow).

Experience with automotive-specific visualization tools (Lichtblick, rerun).

You're comfortable working in a multi-national team with occasional travel for meetings (e.g., PI Planning, ~1x/month). You value diverse perspectives and enjoy working in a hybrid…