At Genmab, we are dedicated to building extra[not]ordinary® futures, together, by developing antibody products and groundbreaking, knock-your-socks-off KYSO antibody medicines® that change lives and the future of cancer treatment and serious diseases. We strive to create, champion and maintain a global workplace where individuals' unique contributions are valued and drive innovative solutions to meet the needs of our patients, care partners, families and employees.
Our people are compassionate, candid, and purposeful, and our business is innovative and rooted in science. We believe that being proudly authentic and determined to be our best is essential to fulfilling our purpose. Yes, our work is incredibly serious and impactful, but we have big ambitions, bring a ton of care to pursuing them, and have a lot of fun while doing so.
Does this inspire you and feel like a fit? Then we would love to have you join us!
The Role
What can past drug development projects tell us about the portfolio we are working on today? Can we use historical data to better understand development timelines, anticipate milestones, and make more informed decisions?
We are looking for a curious and analytically minded Master's student to join our Portfolio and Project Management (PPM) team. In this internship, you will work at the intersection of data science, drug development, and business operations, exploring how data analytics and predictive modelling can support the development of antibody therapeutics.
We have brought together historical project management data in a central data lake and started developing analyses and dashboards. Your project will help us take the next step: moving from understanding past performance towards generating insights and predictions for our current portfolio.
You will explore data relating to development timelines, project milestones, resources, investments, and outcomes. For example, could historical patterns help estimate how long a current project might take to reach its next development milestone? Which characteristics are associated with different timelines or outcomes, and how reliably can we use those relationships to inform predictions?
The specific project scope will be defined together with you, taking into account your interests, statistical and technical background, university requirements, and the team's priorities. The main focus will be on data analytics and predictive modelling, potentially using approaches such as survival analysis to investigate time to development milestones. Depending on the agreed scope, you may also explore how large language models (LLMs) could help colleagues ask questions about portfolio data and access insights more easily.
You will receive joint supervision, combining guidance on the drug development and business context with support on analytical methods. This is an opportunity to strengthen your data science skills while learning how to translate complex analyses into practical insights for a pharmaceutical research and development organization!
Responsibilities
- Explore and assess the quality, completeness, and suitability of historical project and portfolio data for analysis and predictive modelling.
- Work with your supervisors to translate portfolio management questions into a clear research question and feasible analytical approach.
- Analyze patterns and relationships between project characteristics, development timelines, resource use, investments, and outcomes.
- Develop and evaluate statistical or predictive models that could help inform expectations for current projects, such as estimating time to a development milestone.
- Critically assess model performance, assumptions, uncertainty, and limitations, including how well findings may apply to ongoing projects.
- Create clear visualizations, dashboards, or reports that make your findings accessible to colleagues with different backgrounds.
- Depending on the project scope, investigate how LLMs could support natural-language questions about portfolio data, with attention to the accuracy and reliability of their answers.
- Document your methods and code so that others can understand, reproduce, and build on your work.
- Connect your findings to the scientific and operational context of drug development and present recommendations for further analysis or practical use.
- Currently enrolled in a Master's degree at a Dutch university in Data Science, Statistics, Mathematics, Bioinformatics, Computational Biology, or a related quantitative field. Students in Biomedical Sciences or a related life sciences field with a strong statistical and computational background are also encouraged to apply.
- This internship must be a formal, mandatory component of your degree program required for graduation; we cannot consider candidates who have already graduated or who are seeking an extracurricular internship.
- Able to remain enrolled throughout an internship of 6-12 months.
- Affinity with Databricks or other data-lake platforms.
- Experience applying statistical modelling, machine learning, or time-to-event/survival analysis to complex research problems is preferred, particularly where standard methods may need to be adapted or extended. Familiarity with SQL, version control, and cloud data platforms such as Databricks is an advantage.
- A solid foundation in statistics and data analysis, with an interest in applying these skills to predictive modelling.
- Practical experience using Python or R to prepare, analyze, and visualize data, gained through coursework, research projects, or previous internships.
- An understanding of life sciences and an interest in learning how the scientific and operational aspects of drug development influence project progress.
- A critical approach to data, with the ability to question assumptions, investigate unexpected results, and distinguish meaningful findings from patterns that require further validation.
- Able to combine attention to detail with an understanding of the broader question your analysis is intended to answer.
- Strong written and verbal communication skills in English, including the ability to explain analytical findings to colleagues without a data science background.
- A curious, collaborative approach, with the willingness to contribute ideas, ask questions, and take increasing ownership of your project with guidance from your supervisors.
EUR750,00---750,00
The final salary offer will depend on several factors, including your skills, qualifications, and experience.
In addition to base salary, this position is eligible for additional forms of compensation, such as discretionary bonuses and long-term incentives.
When you join Genmab, you become a part of a culture that supports your physical, financial, social, and emotional well-being. Our benefits include, but are not limited to:
- Pension
- Health insurance and wellness benefits
- Paid time off
- Employee support programs
About Genmab
Genmab is an international biotechnology company with a core purpose to improve the lives of patients through innovative and differentiated antibody therapeutics. For 25 years, its hard-working, innovative and collaborative team has invented next-generation antibody technology platforms and harnessed translational, quantitative and data sciences, resulting in a proprietary pipeline including bispecific T-cell engagers, antibody-drug conjugates, next-generation immune checkpoint modulators and effector function-enhanced antibodies. By 2030, Genmab's vision is to transform the lives of people with cancer and other serious diseases with Knock-Your-Socks-Off (KYSO®) antibody medicines.
Established in 1999, Genmab is headquartered in Copenhagen, Denmark with international presence across North America, Europe and Asia Pacific. For more information, please visit Genmab.com and follow us on LinkedIn and X .
Genmab is committed to protecting your personal data and privacy. Please see our privacy policy for handling your data in connection with your application on our website Job Applicant Privacy Notice (genmab.com) .
Please note that if you are applying for a position in the Netherlands, Genmab's policy for all permanently budgeted hires in NL is initially to offer a fixed-term employment contract for a year, if the employee performs well and if the business conditions do not change, renewal for an indefinite term may be considered after the contract.
In overeenstemming