Data Science Specialist, Computational Real-World Evidence (cRWE), Data Science, London

Novo Nordisk
Location
London, London, GB
Job Type
Full-time
Posted
September 24, 2026
Views
75

Job Description

Are you passionate about turning complex real-world patient data into evidence that shapes the future of medicine? Do you thrive at the intersection of data science, human health and strategic decision-making? Join Novo Nordisk as a Data Science Specialist and help drive critical early R&D decisions by applying advanced analytics, machine learning, causal inference and AI to some of the most important questions in drug discovery and development.

Your new role

As a Data Science Specialist, you will be a senior individual contributor within Computational Real-World Evidence (cRWE), helping convert large-scale observational human data into decision-ready evidence that supports disease understanding, target discovery, target maturation and early development decisions.

Working across diverse scientific disciplines, you will provide both hands-on analytical leadership and strategic guidance, ensuring that scientific questions are translated into robust analytical approaches that influence portfolio and pipeline decisions.

Your key responsibilities will include

-

Leading high-priority data science projects that support preclinical and early development decision-making.

-

Developing and implementing analytical and agenticAI approaches across causal inference, statistical modelling, machine learning, deep learning and multimodal data analysis.

-

Translating biological, clinical and portfolio questions into executable analysis plans and actionable evidence.

-

Driving scientific quality, reproducibility and analytical excellence across projects, ensuring appropriate interpretation of uncertainty, bias and causality.

You will work closely with experts across research, biology, epidemiology, translational medicine, clinical development and data science to generate evidence that can meaningfully impact strategic R&D decisions.

Your new department

Computational Real-World Evidence (cRWE) is part of Data Science within the AI & Digital Innovation organisation. The team applies causal inference, advanced statistics, machine learning and artificial intelligence to population-level longitudinal datasets, including electronic health records, claims data, disease registries and large human cohorts.

Our work focuses on the early stages of the R&D value chain, helping scientists better understand diseases, identify patient subgroups, validate targets and strengthen the evidence required before first human dose.

You will join a highly collaborative, international team where scientific curiosity, innovation and methodological excellence are valued equally. The environment offers a unique opportunity to work on complex biomedical questions while contributing to the evolution of advanced data science and agenticAI capabilities across Novo.

Your skills and qualifications

To succeed in this role, you combine deep technical expertise with scientific judgement, strong communication skills and a passion for solving complex healthcare challenges.

We are looking for candidates with

-

A PhD or equivalent research experience in data science, statistics, mathematics, physics, computer science, computational biology or another quantitative discipline.

-

Strong expertise in statistical modelling, machine learning, AI or a related discipline, with demonstrated ability to select and evaluate appropriate methodologies.

-

Significant experience working with longitudinal patient-level datasets such as electronic health records, medical claims, registries or large human cohorts.

-

Significant experience with causal inference, longitudinal modelling, clustering, survival analysis and modern AI approaches relevant to biomedical research.

-

Strong programming skills in Python and/or R, including experience working in cloud-based high-performance computing environments and reproducible research practices.

Are you passionate about turning complex real-world patient data into evidence that shapes the future of medicine? Do you thrive at the intersection of data science, human health and strategic decision-making? Join Novo Nordisk as a Data Science Specialist and help drive critical early R&D decisions by applying advanced analytics, machine learning, causal inference and AI to some of the most important questions in drug discovery and development.

Your new role

As a Data Science Specialist, you will be a senior individual contributor within Computational Real-World Evidence (cRWE), helping convert large-scale observational human data into decision-ready evidence that supports disease understanding, target discovery, target maturation and early development decisions.

Working across diverse scientific disciplines, you will provide both hands-on analytical leadership and strategic guidance, ensuring that scientific questions are translated into robust analytical approaches that influence portfolio and pipeline decisions.

Your key responsibilities will include

-

Leading high-priority data science projects that support preclinical and early development decision-making.

-

Developing and implementing analytical and agenticAI approaches across causal inference, statistical modelling, machine learning, deep learning and multimodal data analysis.

-

Translating biological, clinical and portfolio questions into executable analysis plans and actionable evidence.

-

Driving scientific quality, reproducibility and analytical excellence across projects, ensuring appropriate interpretation of uncertainty, bias and causality.

You will work closely with experts across research, biology, epidemiology, translational medicine, clinical development and data science to generate evidence that can meaningfully impact strategic R&D decisions.

Your new department

Computational Real-World Evidence (cRWE) is part of Data Science within the AI & Digital Innovation organisation. The team applies causal inference, advanced statistics, machine learning and artificial intelligence to population-level longitudinal datasets, including electronic health records, claims data, disease registries and large human cohorts.

Our work focuses on the early stages of the R&D value chain, helping scientists better understand diseases, identify patient subgroups, validate targets and strengthen the evidence required before first human dose.

You will join a highly collaborative, international team where scientific curiosity, innovation and methodological excellence are valued equally. The environment offers a unique opportunity to work on complex biomedical questions while contributing to the evolution of advanced data science and agenticAI capabilities across Novo.

Your skills and qualifications

To succeed in this role, you combine deep technical expertise with scientific judgement, strong communication skills and a passion for solving complex healthcare challenges.

We are looking for candidates with

-

A PhD or equivalent research experience in data science, statistics, mathematics, physics, computer science, computational biology or another quantitative discipline.

-

Strong expertise in statistical modelling, machine learning, AI or a related discipline, with demonstrated ability to select and evaluate appropriate methodologies.

-

Significant experience working with longitudinal patient-level datasets such as electronic health records, medical claims, registries or large human cohorts.

-

Significant experience with causal inference, longitudinal modelling, clustering, survival analysis and modern AI approaches relevant to biomedical research.

-

Strong programming skills in Python and/or R, including experience working in cloud-based high-performance computing environments and reproducible research practices.

In addition, experience supporting drug discovery, translational research, target validation or early development within the pharmaceutical, biotech or technology sectors would be highly advantageous.

Working at Novo

Every day we seek the solutions that defeat serious chronic diseases. To do this, we approach our work with determination, constant curiosity and a commitment to finding better ways forward. For over 100 years, this dedication has driven us to build a company focused on lasting change for long-term health. One where diverse thinking, shared purpose and mutual respect come together to create extraordinary results. When you join us, you're not just starting a job – you're becoming part of a story that spans generations.

What we offer

There is, of course, more on offer here than the uniqueness of our culture and the extraordinary results we produce. Being part of a global healthcare company means opportunities to learn and develop are all around us, while our benefits are designed with your career and life stage in mind.

The placement within the salary range will be assessed during the recruitment process based on the candidate’s skills, competencies, knowledge, and relevant experience.

Incentives and Benefits: The salary package may include short-term and/or long-term incentives as well as other employee benefits based on position level, location, functional area and relevant market benchmarks.

Learn more about our Reward Philosophy here.

Deadline

Apply before 6 October 2026. Applications will be reviewed on an ongoing basis, and we encourage interested candidates to apply as early as possible.

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

Frequently Asked Questions

Where is the job located, and is it remote/hybrid/on-site?
The position is located in London, London, GB. The job posting does not specify a remote, hybrid, or on-site work-mode policy.
What are the key responsibilities of this role?
You will lead high-priority data science projects, develop analytical and agenticAI approaches, translate biological and clinical questions into analysis plans, and drive scientific quality and reproducibility across projects. You will work closely with experts across research, biology, epidemiology, and clinical development to support early R&D decisions.
What qualifications and experience do I need to apply?
You need a PhD or equivalent research experience in a quantitative discipline, strong expertise in statistical modelling, machine learning, or AI, and significant experience with longitudinal patient-level datasets. You also need experience with causal inference, longitudinal modelling, clustering, survival analysis, and strong programming skills in Python and/or R.
What benefits and compensation are offered for this position?
Salary placement is assessed during recruitment based on your skills and experience. The package may include short-term and/or long-term incentives, alongside other employee benefits based on position level, location, functional area, and market benchmarks.
What is the application deadline and process?
The application deadline is 6 October 2026. Applications are reviewed on an ongoing basis, so candidates are encouraged to apply as early as possible.
Which team will I be joining and what is their focus?
You will join the Computational Real-World Evidence (cRWE) team, which is part of Data Science within the AI & Digital Innovation organisation. The team applies causal inference, advanced statistics, machine learning, and AI to population-level longitudinal datasets to support early R&D stages.

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Job Information

Source: manual
AI Relevance: 88/100 (Highly relevant)
Remote Type: onsite
Allowed Locations: Worldwide
Skills & Tags:
novo nordisk machine learning deep learning artificial intelligence computational biology drug discovery data science clinical

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