Portfolio & Project Analytics Intern – Data Science

Genmab; Utrecht; On-site; EUR 8,400 - 10,000; Full time

Benefits offered by this job

Pension

Health insurance

Paid time off

Employee support programs

Job summary

Genmab offers a data analytics internship within the Portfolio and Project Management team in the Netherlands. You will work at the intersection of data science, drug development, and business operations, exploring how predictive modelling can support antibody therapeutics development.

You will receive supervision on both drug development and analytical methods, strengthening data science skills while translating complex analyses into practical insights for a pharmaceutical R&D setting.

Qualifications

• Currently enrolled in a Dutch university for a mandatory internship.
• 6–12 months duration is required for the internship.
• Strong statistical background and programming skills.
• English communication and collaboration with cross-functional teams.

Responsibilities

• Explore and assess the quality and suitability of historical project data for analysis.
• Translate portfolio questions into a clear research plan and feasible methods.
• Analyze relationships between project characteristics, timelines, resources and outcomes.
• Develop and evaluate statistical or predictive models for time-to-milestones.
• Create clear visualizations and dashboards to share findings with non-data colleagues.
• Document methods and code to ensure reproducibility and transferability.

Skills

Databricks

Python

R

Survival analysis

SQL

Team communication

Critical thinking

Education

Master’s degree in Data Science / Statistics

Tools

SQL

Git

Databricks

Job description

Genmab offers a data analytics internship within the Portfolio and Project Management team in the Netherlands. You will work at the intersection of data science, drug development, and business operations, exploring how predictive modelling can support antibody therapeutics development.

You will receive supervision on both drug development and analytical methods, strengthening data science skills while translating complex analyses into practical insights for a pharmaceutical R&D setting.