Epidemic Modeller & Data Scientist

CEPI (Coalition for Epidemic Preparedness Innovations); City Of London; On-site; GBP 45,000 - 65,000; Full time

Job summary

A global health organization based in London is seeking a Modeller and Data Scientist for a 12-month full-time fixed-term contract. The role involves advanced data analysis techniques to support vaccine development and preparedness against outbreaks. Candidates should possess an MSc or PhD in a related field and at least three years of experience. Strong skills in R and Git are essential, with familiarity in Python being preferred. The position offers an inclusive environment and the chance to work on significant global health challenges.

Benefits

Opportunity to work with leading experts

Experience in vaccine development

Diverse and inclusive working environment

Qualifications

• Strong quantitative background with an advanced degree.
• At least three years of relevant experience.
• Experience in outbreak analytics or epidemiological forecasting.

Responsibilities

• Prepare and clean datasets for modelling.
• Define quantitative thresholds for outbreak response.
• Run validated model templates and provide timely outputs.

Skills

Applied quantitative analysis

Statistical methods

Mathematical modelling

Introductory machine learning

R

Git and GitHub

Education

MSc in data science, mathematical modelling, infectious disease epidemiology, computer science, biostatistics

PhD (newly qualified)

Tools

Python

Job description

A global health organization based in London is seeking a Modeller and Data Scientist for a 12-month full-time fixed-term contract. The role involves advanced data analysis techniques to support vaccine development and preparedness against outbreaks. Candidates should possess an MSc or PhD in a related field and at least three years of experience. Strong skills in R and Git are essential, with familiarity in Python being preferred. The position offers an inclusive environment and the chance to work on significant global health challenges.