To succeed as a Data Scientist at Novo Nordisk, you need to excel in several distinct evaluation areas. The process is designed to test not just what you know, but how you apply it and communicate it.
Technical and Data Science Knowledge
This area forms the baseline of your evaluation. Interviewers need to know that you possess the mathematical and programmatic skills required to handle complex datasets and build robust models. Strong performance here means writing clean, efficient code and demonstrating a deep understanding of the assumptions, limitations, and appropriate applications of various machine learning algorithms.
Be ready to go over:
- Statistical Foundations – Hypothesis testing, A/B testing, probability distributions, and experimental design, which are particularly critical in a life sciences context.
- Machine Learning Algorithms – The theory and application of supervised and unsupervised learning, including tree-based models, regression, clustering, and potentially deep learning depending on the team.
- Data Manipulation and Coding – Proficiency in Python or R, SQL for data extraction, and libraries like Pandas, Scikit-learn, or PyTorch.
- Advanced concepts (less common) – Survival analysis, causal inference, and natural language processing (NLP) for processing medical literature or real-world evidence.
Example questions or scenarios:
- "Explain the trade-offs between a Random Forest and a Gradient Boosting model for predicting patient adherence."
- "Write a SQL query to extract and aggregate patient diagnostic codes from a relational database."
- "How would you handle a dataset with severe class imbalance, such as predicting a rare adverse event?"
Presentation and Communication Skills
Novo Nordisk places a massive emphasis on how well you can communicate your findings. You will likely be asked to present a past project or the results of a take-home case study. Strong performance means delivering a clear, engaging narrative that highlights the business or clinical impact of your work, rather than just listing the technical steps you took.
Be ready to go over:
- Project Framing – Clearly articulating the problem statement, the objective, and why the project mattered to the organization.
- Methodology Explanation – Explaining complex models in a way that is accessible to non-technical stakeholders without losing technical accuracy.
- Impact and Recommendations – Translating model outputs into actionable business or clinical recommendations.
Example questions or scenarios:
- "Present a past data science project: focus on the problem, your approach, and the ultimate impact."
- "How would you explain the concept of a p-value to a commercial manager who has no background in statistics?"
- "Walk us through the conclusions of your case study and defend your recommendations against alternative approaches."
Case Studies and Group Tasks
For many Data Scientist roles at Novo Nordisk, you will face a structured case study, which may sometimes be conducted as a group task. This evaluates your real-time problem-solving, teamwork, and ability to navigate ambiguous scenarios under time pressure. A strong candidate takes a structured approach, actively listens to peers (if in a group), and focuses on delivering a pragmatic solution.
Be ready to go over:
- Structured Problem Solving – Breaking down a high-level business or clinical problem into manageable analytical steps.
- Collaborative Execution – Working effectively with others, delegating tasks, and synthesizing different viewpoints into a cohesive strategy.
- Time Management – Delivering a complete, presentable solution within a strict timeframe (e.g., a 4-hour window).
Example questions or scenarios:
- "Given this anonymized dataset of supply chain logistics, identify the bottlenecks and propose a predictive model to mitigate future delays."
- "Work with your group to design a data strategy for launching a new digital health companion app."
- "Present your case study findings to the assessment panel and answer rapid-fire questions on your methodology."
Behavioral and Cultural Fit
Your alignment with the "Novo Nordisk Way" is critical. Interviewers, including HR and hiring managers, will assess your motivation, empathy, and working style. Strong performance in this area involves showing self-awareness, a genuine passion for improving patient lives, and a track record of positive collaboration.
Be ready to go over:
- Cross-Functional Collaboration – Examples of how you have worked with engineers, product managers, or domain experts.
- Handling Ambiguity and Failure – How you pivot when a model fails or when data is unavailable.
- Motivation and Alignment – Why you are specifically interested in healthcare and Novo Nordisk.
Example questions or scenarios:
- "Tell me about a time you had a disagreement with a stakeholder regarding a technical approach. How did you resolve it?"
- "Describe a situation where your initial hypothesis was proven wrong by the data. What did you do next?"
- "Why do you want to transition your career into the pharmaceutical industry?"
