External Manufacturing & Supply Business Data Analyst VIE

Job Description

External Manufacturing & Supply Business Data Analyst | Sanofi

The Tone:
This is an international development program (VIE Contract) at Sanofi, located in Framingham, United States. Sanofi is an R&D-driven, AI-powered biopharma company committed to improving people’s lives by inventing medicines and vaccines that treat and protect millions globally. This role is crucial for reimagining how life-changing treatments reach people everywhere, faster, by helping to drive the External Manufacturing & Supply data strategy forward. Join a global network that powers how Sanofi delivers seamlessly and purposefully.

The TL;DR
• Role: Internship
• Type: Contract
• Location: In-person, Framingham, MA

• Team: Digital Data & Technology team, specifically AI, Data Foundations & Analytics team
• Mission: Own deliverables, contribute to cross-functional discussions, and help drive the External Manufacturing & Supply data strategy forward.
• Tech Stack: Python, SQL, Power BI, Dataiku, Snowflake, AWS, GitHub, scikit-learn, pandas, NumPy, Streamlit

What You’ll Actually Do
• Project Contribution: Contribute to data analytics projects across the EM&S organization, from scoping through delivery.
• Development & Maintenance: Develop and maintain data pipelines, dashboards, and reports with limited supervision.
• Cross-functional Collaboration: Actively participate in cross-functional meetings and contribute to project discussions.
• Business Solution Translation: Collaborate with Supply Chain, Quality, Finance, and Digital teams to translate business needs into data solutions.
• Database Contribution: Contribute to the development and maintenance of EM&S databases and reporting environments (Snowflake, Power BI).

The Must-Haves
• Background: Master’s degree in Data Science, Computer Science or a related field.
• Experience: Minimum of one significant internship or equivalent academic project demonstrating end-to-end work on a data science or analytics initiative; demonstrated ability to contribute to data engineering or analytics projects with some independence; familiarity with agile working methods and collaborative development environments.
• Skills: Solid proficiency in Python programming for data engineering and analytics; good working knowledge of SQL and relational databases; experience with data visualization tools (Power BI, Dataiku, or similar); familiarity with cloud platforms, particularly Snowflake and AWS; experience with GitHub and version control practices.
• Bonus: Basic understanding of pharmaceutical or manufacturing operations; exposure to machine learning frameworks (scikit-learn, pandas, NumPy); familiarity with Streamlit or similar application development tools.