You have a strong quantitative background, with a Master’s or Ph.D. in Statistics, Mathematics, Data Science, Computer Science, or a related field, along with 5+ years of experience in a data science or similar role. You are comfortable leading by example, guiding others, setting technical direction, and raising the quality of analytical work across teams.
You bring an experimental mindset, balancing speed and rigor to iterate quickly and deliver impact. You have experience owning machine learning or analytical projects end-to-end, from ideation through to deployment, and you are able to clearly communicate insights to non-technical stakeholders.
You likely have experience in several of these areas:
- Strong experience with Python and solid understanding of software and data engineering practices for production systems
- Strong familiarity with the standard data science toolkit (e.g., pyspark, Pandas, Scipy, Numpy etc.)
- You have experience building data pipelines on platforms such as Databricks or Snowflake
- Theoretical understanding and practical experience in statistical modeling, inference, time-series analysis, and machine learning algorithms
- Understanding of CI/CD principles, particularly for data or ML pipelines
Experience with software versioning (e.g., Git)
- Experience with generative AI or LLM-based applications
Beneficial:
- Experience or familiarity with front-end development (e.g., Streamlit or React)
- Experience with cloud-environments ‑ (preferably Azure)
- Automotive or mechatronic domain knowledge
- Experience mentoring or leading technical work
You would thrive in a collaborative environment while feeling confident driving technical direction. You would lead through knowledge‑sharing, encouragement, and clarity as well as communicate effectively with diverse audiences. You bring curiosity, creativity, and strong analytical rigor. You inspire others through initiative, openness, and responsibility. You bring your experience in shaping processes, methods, and standards.
