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A mobility technology company in Berlin is seeking a Data Scientist to develop models for validating autonomous driving systems. The ideal candidate will analyze complex data and collaborate with cross-functional teams to ensure safety and compliance in vehicle behavior. Proficiency in Python, SQL, and a background in data science or machine learning is essential. The role offers a hybrid work setup with competitive benefits, including flexible working hours and mental health support.
Berlin, 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 Vision and 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:
We are a member of Charta der Vielfalt and are dedicated to actively fostering a workplace that celebrates and promotes diversity in various aspects such as age, gender identity, race, sexual orientation, physical or cognitive ability, and ethnicity. At MOIA, we embrace a culture where people are accepted, respected, valued, appreciated, and included.
In our commitment to promoting diversity and inclusivity, we regularly provide unconscious bias training to all our employees. Furthermore, we continuously strive to enhance our hiring process by ensuring a diverse hiring panel.
Since we love to collaborate, it is clear to us that we don't want to become a fully remote company, but we also don't need to spend every day of the week in the office to do a great job.
Our current hybrid work approach focuses on adapting to different needs, including increased flexibility that works best for the teams and the individuals with as much self-determination as possible.
Get more insights on how we work on our blog to find out more about our hiring process or follow us on Instagram for a look inside MOIA.
At MOIA we’re reimagining the future of mobility – safe, autonomous and tailored to the needs of cities and their people. As a tech company with more than 400 employees, we build mobility solutions that truly move cities forward.
We launched our ridepooling service in Hamburg in 2019 and have been part of the city’s public transport system since 2023. Since launch, we have transported over 12 million passengers. Currently, MOIA is evolving from a mobility provider to a tech provider offering a scalable and safe turnkey solution for autonomous driving.
With office locations in Berlin and Hamburg, our diverse and international team comprising more than 60 nationalities works together toward that shared mission.
MOIA is more than a technology provider – we are a partner to cities and public transport operators committed to creating more livable spaces and delivering mobility solutions that are reliable, safe and comfortable.
We value authenticity and personal insights in your application responses. While AI tools can be useful, we encourage you to answer the following questions based on your own experiences and understanding. This helps us keep a human touch and better evaluate your unique perspective and match for the role.
To reinforce an unbiased screening process, we kindly ask you not to include your picture, age, address, or any other details unrelated to your qualifications and suitability for the role. Additionally, we anonymize applications during the initial review phase by removing personally identifiable information. This ensures that our evaluation focuses solely on your skills, experience, and potential – supporting a fair and inclusive hiring experience for all candidates.