Data Scientist, EU Analytics for Life Sciences AI

Veeva; Barcelona; Remote; EUR 48,000 - 75,000; Full time

Benefits offered by this job

Work Anywhere

Career progression

Equity in Veeva

Job summary

Veeva is building the industry cloud for Life Sciences across Europe. As a Data Scientist in our EU Analytics practice, you will transform how customers work with Technology, Data, and AI, building advanced analytical models and integrating Veeva Data Cloud with European healthcare data assets.

You will collaborate with product managers, data engineers, and consultants to deliver end-to-end analytics solutions, applying ML methods to high-impact business questions, and documenting methodologies

Qualifications

• 2+ years of experience in data science or ML roles, preferably in Life Sciences or healthcare analytics.
• Strong problem-solving and communication skills with cross-functional collaboration.
• Proficiency in Python and SQL; ability to translate technical challenges to non-technical stakeholders.

Responsibilities

• Design, prototype, and scale advanced analytics solutions for Life Sciences clients across Europe.
• Integrate Veeva Data Cloud with European healthcare data assets and ensure actionable insights.
• Develop statistical methods and ML models to address high-impact business questions.
• Collaborate with product, data engineers, and consultants to deliver end-to-end analytics.
• Document methodologies, architectures, and validation processes for defensibility and reuse.

Skills

Python

SQL

Data science

Communication

Documentation

Education

MS/PhD in Computer Science, Statistics, Data Science, Mathematics

Tools

Apache Airflow

AWS

Data visualization tools

Job description

Veeva is building the industry cloud for Life Sciences across Europe. As a Data Scientist in our EU Analytics practice, you will transform how customers work with Technology, Data, and AI, building advanced analytical models and integrating Veeva Data Cloud with European healthcare data assets.

You will collaborate with product managers, data engineers, and consultants to deliver end-to-end analytics solutions, applying ML methods to high-impact business questions, and documenting methodologies