Modeller and Data Scientist

CEPI (Coalition for Epidemic Preparedness Innovations); Greater London; On-site; GBP 40,000 - 60,000; Full time

Job summary

A global health organization is seeking a quantitative analyst with an MSc or recent PhD in fields like data science or epidemiology. The candidate should have 3+ years of relevant experience and be adept in R and Git, with a commitment to working in a cross-functional team. Responsibilities include preparing and analyzing datasets to support outbreak forecasts and decisions. The role is based in London, UK, with some travel requirements. This position offers a chance to contribute to global vaccine development efforts.

Benefits

Opportunity to work with leading experts

Diverse and inclusive environment

Experience in global vaccine development efforts

Qualifications

• 3+ years of experience in outbreak analytics or epidemiological forecasting.
• Proficiency in R, Git, and GitHub with a willingness to learn Python.
• Experience providing decision-ready analyses.

Responsibilities

• Prepare and clean datasets for modelling and conduct preliminary analyses.
• Define quantitative thresholds for outbreak response.
• Compile and analyze disease burden and vaccine impact data.

Skills

Applied quantitative analysis

Statistical methods

Mathematical modelling

Machine learning

R

Git

GitHub

Python

Education

MSc or PhD in data science or related field

Job description

The role

requires someone who is proactive, self-sufficient, and able to work effectively within a cross-functional team as well as independently.

We are looking for candidates who bring a strong quantitative background with an advanced degree (MSc or newly qualified PhD) in data science, mathematical modelling, infectious disease epidemiology, computer science, biostatistics or a closely related field. They should have at least three years of relevant experience and be prepared to work in a matrixed, cross-functional environment. The ideal candidate will have solid skills in applied quantitative analysis, including statistical methods, mathematical modelling, and introductory machine learning, and experience in outbreak analytics or epidemiological forecasting. Competency in R alongside Git and Github is essential, with either working knowledge of Python or a clear willingness to learn.

The post-holder will report directly to the Head of Data Science and Advanced Analysis and work closely with members of the team as well as collaborate across the Epidemiology and Data Science department.

Responsibilities

Rapid Response Modelling

• Prepare and clean surveillance, genomic, and outbreak datasets early, using best judgement to anticipate what will be needed for modelling. This includes running preliminary analyses or engaging relevant country modellers ahead of formal requests.
• With departmental input, define quantitative thresholds for triggering CEPIs outbreak response
• Maintain version control and documentation for CEPI’s model repository, ensuring workflows remain up to date and ready for rapid activation.
• Run validated and documented model templates under supervision and provide timely outputs that support outbreak forecasts, scenario analysis, and rapid risk assessments
• Contribute to the design, execution, and reporting of simulation exercises by proactively identifying gaps, making improvements, and providing required inputs.
• Summarise model outputs for internal briefs, dashboards, and decision documents, and surface key insights without waiting for prompts.

Knowledge and Evidence Generation

• Compile disease burden, stockpile, and vaccine-impact data for forecasting, portfolio planning, and CEPI’s 100 Days Mission metrics.
• Conduct basic statistical analyses and produce clear visual outputs in R or Python.
• Support the development, testing, and documentation of AI and predictive modelling pipelines.
• Contribute to evidence summaries, technical notes, and rapid analyses for R&D RDP, Clinical Development, Regulatory) and other internal stakeholders

Strategic Modelling Partnerships

• Provide analytical and coordination support to CEPI’s modelling network and regional modelling partners including Africa CDC, PAHO, ICMR, and other networks.
• Prepare partner data templates, manage collaborative workspaces, and ensure quality control of shared datasets.
• Track outputs from regional outbreak modelling exercises and consolidate lessons learned.
• Support monitoring and evaluation for modelling partnerships.
• Contribute to external engagement through slide preparation, meeting coordination, and drafting policy briefs.
• Help strengthen the visibility of CEPI’s modelling partnerships and connect internal teams with regional networks.

Cross-Functional and Internal Support

• Support delivery of the DSAA and E&DS strategy with analytical inputs and operational support.
• Provide disease-specific analyses for priority pathogens including Lassa, Chikungunya, H5N1, RVF, SARS-CoV-2, and novel pathogens.
• Support CEPI’s supply-chain and vaccine deployment modelling initiatives.
• Assist with CEPI’s climate-health analytical work, where relevant.
• Participate in internal emergency response structures and provide modelling support when required.
• Contribute to internal and external workshops designed to strengthen predictive modelling capacity and shape future DSAA plans.
• Perform other duties that support the smooth functioning of the DSAA work programme.
• Represent CEPI in external scientific and technical discussions with partners and stakeholders
• Provide modelling and operational support to senior DSAA team members when required.
• Provide statistical support to study design and analyses to the wider department, including input into observational and RWE studies when required when required.

Education, Experience and Competence

Essential

• MSc or recent PhD in data science, modelling, epidemiology, computer science, biostatistics, or a related quantitative field.
• 1-3 years’ experience in outbreak analytics, epidemic forecasting, or epidemiological modelling
• Proficient in R, Git, and GitHub; working knowledge of Python or willingness to learn.
• Proven ability to manage multiple tasks at pace with strong organisational and time management skills.
• Experience providing decision-ready analyses to public health or research settings.
• Strong written and verbal communication skills, with the ability to translate technical concepts for non-technical audiences.
• Understanding of infectious disease transmission, vaccine-impact modelling, and global preparedness needs.
• Awareness of AI / ML applications in biomedical or epidemiological domains.
• Ability to collaborate effectively across geographic regions and disciplines.
• High degree of initiative, problem-solving ability, and adaptability.

Desirable

• Experience in vaccine development or vaccine-related research.
• Experience working in a matrixed cross-functional teams.
• Familiarity with vaccine stockpile and demand modelling.
• Understanding of data sharing challenges, model validation needs, and responsible AI considerations.
• Experience with climate-health interactions or One Health approaches.
• Previous work within emergency response, rapid risk assessment, or operational public health analytics.

Travel and Location Requirements

• This position must be based in London, UK or Oslo, Norway.
• Relocation assistance and work visa sponsorship are not available for this fixed-term position.
• International travel up to 10%.

What we can offer you

• The opportunity to work together with leading experts on solutions for global challenges
• Experience in the international effort on developing vaccines against emerging infectious diseases and accelerating vaccine development response to outbreaks
• A diverse and inclusive working environment