Lead Data Scientist

Novo Nordisk A/S; Ballerup; Remote; DKK 743,000 - 1,092,000; Full time

Job summary

Novo Nordisk A/S is seeking a Lead Data Scientist to set the technical direction for AI, data science, and ML that drives autonomous, data-driven supply chain decisions. You will build forecasting, optimization and GenAI use cases end-to-end with a delivery team and take them into production to improve network efficiency and no-touch planning.

The role requires strong Python/SQL skills, experience with Databricks, Unity Catalog, CI/CD, and a track record of delivering AI solutions in production.

Qualifications

• Several years of experience developing and deploying data science, machine learning or AI models using real business data.
• Strong Python and SQL skills, with a solid understanding of model validation, interpretation, uncertainty and business impact.
• Hands-on experience with Databricks, Unity Catalog and data pipelines, including data organised in a medallion architecture.
• Experience working in a CI/CD setup and writing reusable, testable and documented code.
• An understanding of reliability, monitoring, versioning, security, access control and maintainability of AI applications.
• Knowledge of LLM evaluation, guardrails and observability, for example using tools such as Langfuse or Grafana.
• The ability to work independently with both technical teams and business stakeholders, and to explain complex findings clearly.
• An MSc, PhD or equivalent practical experience in a relevant quantitative field.

Responsibilities

• Partner with Supply Chain stakeholders and delivery team to scope business problems, choose the right methods and define how success will be measured.
• Set the data science direction across the use case portfolio, shape solution architecture with the Tech Lead, coach junior data scientists and review work delivered by external vendors.
• Develop statistical, machine learning and AI models for forecasting, network optimisation, recommendations and workflow automation – including RAG applications, assistants and agentic workflows where the use case calls for them.
• Build data and model pipelines in Databricks, using Unity Catalog for data governance and a medallion architecture to organise data.
• Take models into production through GitHub Actions CI/CD pipelines, with automated testing, experiment tracking, model registries, documentation and ongoing monitoring – applying the right validation, traceability, access control and change control along the way.
• Evaluate technical performance and business impact, be clear about uncertainty and limitations, and work with AI Engineers to integrate what you build into products and operational workflows.

Skills

Python

SQL

Databricks

CI/CD

Langfuse or Grafana

LLM evaluation & observability

Stakeholder communication

Data pipelines

MLOps familiarity

Education

MSc or PhD in a quantitative field

Tools

GitHub Actions

Langfuse

Grafana

Azure

AWS

Job description

Department: Supply Chain AI Solutions, Enterprise AI, Enterprise IT & Quality

Your impact begins here

As Lead Data Scientist, you will set the technical direction for AI, Data Science, and machine learning that that enables our supply chain processes to become more autonomous, and data driven. You will build forecasting, optimisation and GenAI use cases end-to-end with a delivery team and take them into production, helping move us towards better network optimisation and no-touch planning. Your work will strengthen the real operational decisions that help high-quality medicines reach the millions of people living with serious chronic diseases.

What you’ll bring

• Several years of experience developing and deploying data science, machine learning or AI models using real business data.
• Strong Python and SQL skills, with a solid understanding of model validation, interpretation, uncertainty and business impact.
• Hands-on experience with Databricks, Unity Catalog and data pipelines, including data organised in a medallion architecture.
• Experience working in a CI/CD setup and writing reusable, testable and documented code.
• An understanding of reliability, monitoring, versioning, security, access control and maintainability of AI applications.
• Knowledge of LLM evaluation, guardrails and observability, for example using tools such as Langfuse or Grafana.
• The ability to work independently with both technical teams and business stakeholders, and to explain complex findings clearly.
• An MSc, PhD or equivalent practical experience in a relevant quantitative field.

Useful, but not essential:

• Experience from pharma, life sciences or supply chain.

What you’ll do

You will be both advisor and hands‑on builder: shaping which problems are worth solving, then building what solves them in production.

• Partner with Supply Chain stakeholders and delivery team to scope business problems, choose the right methods and define how success will be measured.
• Set the data science direction across the use case portfolio, shape solution architecture with the Tech Lead, coach junior data scientists and review work delivered by external vendors.
• Develop statistical, machine learning and AI models for forecasting, network optimisation, recommendations and workflow automation – including RAG applications, assistants and agentic workflows where the use case calls for them.
• Build data and model pipelines in Databricks, using Unity Catalog for data governance and a medallion architecture to organise data.
• Take models into production through GitHub Actions CI/CD pipelines, with automated testing, experiment tracking, model registries, documentation and ongoing monitoring – applying the right validation, traceability, access control and change control along the way.
• Evaluate technical performance and business impact, be clear about uncertainty and limitations, and work with AI Engineers to integrate what you build into products and operational workflows.

Who you’ll work with

You will join Supply Chain AI Solutions, a small, end‑to‑end team within Enterprise AI, part of Enterprise IT & Quality – where colleagues work across the Novo value chain, close to the stakeholders they support.

In your team, data scientists, and engineers work side by side, combining analytical depth with the engineering capability needed to get models into production. You will work closely with the Tech Lead, AI Engineers and junior data scientists, and embed directly with Supply Chain domain experts and colleagues in the commercial organisation – so ideas move quickly from problem to working tool.

The team is cloud‑native, using Databricks, Azure and AWS, and values agility, diverse thinking, continuous learning and practical work that improves real operational decisions.

What you can expect here

You will be trusted to set direction and make your voice heard, in a team culture built on feedback, honesty and fun. You will work at the forefront of AI and technology at Novo, at a time when we are upskilling our entire workforce to advance AI as a main driver for innovation for people living with serious chronic diseases.

You can expect continuous learning, career development and benefits tailored to your life and career stage.

Annual base salary ranges from 742,600 to 1,091,600 DKK, corresponding to the level of the position. Placement within the range will be assessed during recruitment based on skills, competencies, knowledge and relevant experience. The salary package may include short- and/or long-term incentives and other employee benefits based on position level, location, functional area and relevant market benchmarks. Learn more about our Reward Philosophy at www.novonordisk.com/careers/working-at-novo-nordisk/total-rewards-benefits.html.

We commit to an inclusive recruitment process and equality of opportunity for all our job applicants.