Senior Data Scientist - Real-World Data

The position 

The department of Computational Precision Health is being established to support decision-making and drug discovery in Research & Early Development. We are looking for a highly motivated and skilled Senior Data Scientist to work with Real-World Data.

You will contribute analytical and advanced programming skills to a team of data scientists and epidemiologists that, together with stakeholders from across the organisation, create actionable insights and evidence from real-world data. Our data comes from academic-industry partnerships, in-licensed databases of electronic medical records or health insurance claims, observational studies, and many other sources. 

Your main responsibilities will be to:

Apply state-of-the art methods within statistical analysis, programming, and visualisation to generate insights and knowledge from our large and diverse data sources.

Create user-friendly dashboards. 

Participate in designing, planning, developing, and documenting studies to make informed decisions based on data. 

Write, document, and maintain code in R and SQL to transform, standardise and aggregate data to create analysis-ready data sets from large amounts of raw data. 

Evaluate data quality of potential new data sets. 

Qualifications 

We emphasise accountability and reaching goals through a collaborative effort, thus it is essential that you use your good interpersonal and communication skills to achieve results together with others. You will enjoy responsibility and complete your assignments proactively and within timelines.

To be successful in the role we expect you to have master’s degree in Life sciences e.g. Biostatistics, Mathematics, Physics, Computer Science, Data Science or equivalent together with experience in managing, analysing, documenting, and programming comprehensive data. 

In the right candidate, we ware looking for 

Experience with real world data (RWD), such as medical records or health insurance claims. 

Expertise in classical statistical methods such as regression analyses and survival analyses (including competing risk). 

Experience in advanced analytical methods such as machine learning approaches. 

Quickly understand stakeholder needs and translate those into solutions and results through programming and analyses. 

Strong programming skills and experience with transforming millions of rows of data by writing advanced, well-performing and maintainable code in R, python or similar. 

Fluent communication in English, both written and spoken. 

Additionally, we would welcome, not essentially but preferably, PhD degree in a relevant field with complementing experience from the pharmaceutical industry or consultancy. Experience with statistical methods on causal inference and with SQL would be good to have, along with hands on knowledge in git, Linux, when creating dashboards using R/Shiny or other software, project coordination and technical writing. 

About the department 

The department of Computational Precision Health (CPH) has presence in Mølåv/Hellerup (Denmark) and London (UK).

CPH is part of the Artificial Intelligence and Digital Research (AIDR) area, which sits within the wider Digital Science & Innovation (DSI) organisation. DSI is supporting the digital journey across all our therapy areas in Novo Nordisk Research and Early Development. The CPH department focuses on insights and causal relationships from real-world data through advanced statistical and machine learning methods. We analyse many different data sources to generate evidence to support drug discovery, preclinical and early clinical drug development projects.