Data Scientist
Pubblicato il 01-08-2026 - Stellantis in Italia
ABOUT THE ROLE We are currently looking for a Data Scientist with strong technical skills and 3–5 years of relevant professional experience in data analytics or data science roles .
This position is ideal for someone who enjoys hands‑on work with large datasets and is comfortable working with code, advanced analytics, and modeling responsibilities.
You will take ownership of an existing Python-based pricing algorithm (developed in collaboration with a leading consultancy) and help bring structure and clarity to our data through Power BI dashboards and reporting . At the same time, this role represents a strategic investment in the future of our analytics capabilities.
KEY RESPONSIBILITIES
- Learn, maintain, and further develop our Micro Clustering Pricing Algorithm written in Python. It is therefore essential to be comfortable coding in Python , and beneficial to have a basic understanding of machine learning concepts and the underlying mathematics.
- Build and maintain Power BI dashboards and reports using data from multiple sources including ERP systems, Excel, and pricing platforms .
- Support the Global Pricing Team with data preparation, transformation, and visual storytelling .
- Help identify margin leakage, pricing improvement opportunities, and commercial performance trends .
- Translate business needs into data-driven solutions while ensuring consistency across tools and reports.
- Apply data-driven insights to solve business problems and improve decision‑making.
WHO YOU ARE
- Bachelor’s or Master’s degree in Data Science, Engineering, Economics, Computer Science, or a related field.
- 3–5 years of experience in data analytics, data science, or a related field, with proven hands‑on involvement in data‑driven projects.
- Proficient in Python , with experience maintaining or adapting existing codebases.
- Solid experience building interactive dashboards in Power BI , with hands‑on responsibility for ETL and data cleansing .
- Familiarity with SQL, R , or si