Senior/Lead Data Scientist

Enterprise IT & Quality

Novo Nordisk Global Business Services(GBS)

Build end-to-end AI/ML solutions that shape commercial decisions at Novo Nordisk from forecasting and causal inference to GenAI assistants and agentic workflows. If you love taking models all the way to production and working shoulder-to-shoulder with the people who use them, read on.

Your new role

Youll join the Commercial Data Science & AI team to develop and scale advanced analytics, machine learning and AI across our commercial organisation. As a Senior/Lead Data Scientist, youll build end-to-end AI/ML solutions from forecasting and econometrics to GenAI systems (RAG, assistants, agentic workflows) and take them all the way to production. Youll embed directly with domain experts as both advisor and hands-on builder, working closely with commercial stakeholders and AI Engineers on platforms such as Databricks, Snowflake and Azure.

Your responsibilities will include:

• Translating commercial business questions into data science, machine learning and model-production solutions
• Developing and deploying statistical, econometric and machine-learning models for commercial use cases forecasting, segmentation, targeting, propensity, experimentation, causal inference and commercial optimisation
• Building and shipping GenAI applications end-to-end RAG solutions, GenAI assistants and agentic or workflow-based automation
• Evaluating model performance with appropriate statistical, ML and business metrics, and explaining assumptions, limitations, uncertainty and recommendations to non-technical stakeholders
• Taking your work to production: version control, reusable and tested code, documentation and MLOps best practice including experiment tracking, model registries and monitoring
• Collaborating with AI Engineers and platform teams where models are integrated into AI products or user-facing solutions
• Independently scoping complex commercial problems, choosing appropriate methods, and helping set best practice for commercial decision science and productionisation
• Leading technical projects and mentoring team members

Your new department

In Enterprise IT & Quality, you will be part of a business area that drives impact across the full Novo Nordisk value chain. We strive to stay close to our stakeholders in the business to ensure we deliver on their needs, helping reach millions of people living with serious chronic diseases. Our focus is on being at the forefront within our three areas; ensuring the highest quality for patients, being a trusted tech leader and an environmentally responsible business.

Youll sit within Enterprise AI, in a small, end-to-end Commercial Data Science & AI team where scientists and engineers work side by side you own the modelling, and youre never far from the engineering help that gets it live. Were cloud-native (Databricks, Snowflake, Azure) and value agility, diverse thinking and continuous learning in a culture built on feedback, honesty and fun.

Your skills & qualifications

Were looking for people with deep expertise in one or more of: statistics, econometrics, forecasting, causal inference, segmentation or applied/commercial ML; and/or model production and MLOps; and/or GenAI engineering LLM applications, RAG and agents.

Youll bring:

• Several years experience developing, deploying or supporting data science, machine learning, statistical or AI models on real commercial or business data
• Strong Python and SQL, with good coding practice (Git, documentation, reusable and tested code), and a strong background in model validation, interpretation, uncertainty and business impact
• The ability to communicate clearly with both technical and non-technical stakeholders, and a genuine interest in solving commercial problems not only technical modelling ones
• An AI-native way of working, comfortable with AI-assisted development tooling (Cursor, Claude Code, GitHub Copilot)
• An MSc, PhD or equivalent practical experience in statistics, econometrics, data science, mathematics, computer science, engineering or a related quantitative field

Depending on your strengths, youll bring depth in several of:

• Practical MLOps CI/CD for models, model registries and experiment tracking (e.g. MLflow), and model monitoring
• Hands-on GenAI LLM applications, RAG (embeddings, vector search, retrieval and evaluation), prompt engineering, and agentic/workflow-based solutions
• APIs and backend development, testing and CI/CD
• Deploying models with GitHub Actions or Azure DevOps

It would be an advantage if you also bring some of:

• A track record of taking work to production whether classical models or AI applications and a solid understanding of production concerns: reliability, monitoring, versioning, security, access control and maintainability
• LLM evaluation, prompt/version management, guardrails and observability (e.g. LangFuse / LangSmith); monitoring quality, latency, reliability and cost of AI products
• Experience from pharma, healthcare, life sciences or commercial analytics and consumer behavior

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.