- Company Name
- CAPGEMINI ENGINEERING
- Job Title
- Data Scientist - Automotive field
- Job Description
-
Job title: Data Scientist – Automotive
Role Summary: Design, build, and deploy data‑centric solutions that enable data‑driven decision making for automotive business units across Europe. Lead end‑to‑end modeling, MLOps, and visualization work, translating complex datasets into actionable insights for stakeholders.
Expectations: Deliver robust predictive and analytical models that improve product performance, operational efficiency, and customer experience. Demonstrate clear communication of results and maintain high standards of data quality, reproducibility, and scalability.
Key Responsibilities
- Preprocess and analyze large structured and unstructured automotive datasets using Python and SQL
- Build predictive models (tabular, time‑series, NLP) and anomaly detection systems, validate with statistical rigor
- Develop recommendation engines and optimization scripts tailored to automotive processes
- Create interactive dashboards and visualizations (e.g., Streamlit, Dash) for cross‑functional teams
- Implement MLOps pipelines: version control, testing, deployment, monitoring, and scaling on cloud infrastructure
- Collaborate with data architects to design data models in Snowflake and ensure integration with enterprise systems
- Document modeling methodology, performance metrics, and maintenance procedures for reproducibility
Required Skills
- Advanced programming in Python (data science libraries: pandas, scikit‑learn, TensorFlow/PyTorch, statsmodels)
- SQL proficiency, including complex queries and performance tuning
- Experience with Dataiku DSS (Designer, Advanced Designer, ML Practitioner, Developer paths)
- Familiarity with web frameworks for dashboards (Streamlit, Dash)
- Knowledge of MLOps concepts: CI/CD, containerization, model versioning, monitoring
- Strong statistical and machine learning foundations (regression, classification, time‑series, NLP, clustering)
- Clear communication of technical results to non‑technical stakeholders
Required Education & Certifications
- Master’s degree in Engineering, Mathematics, Statistics, Computer Science, or related field
- Minimum 2 years of professional data science experience
- Dataiku DSS certifications: Core Designer Path, Advanced Designer Path, ML Practitioner Path, Developer Path
- Experience with Snowflake data warehouse and data architecture principles
- Automotive industry domain knowledge is a plus.