Senior Data Scientist at Medicines and Healthcare Regulatory Agency

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

20 May, 26

Salary

0.0

Posted On

19 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Leadership, Data Science, Machine Learning, Artificial Intelligence, Simulation Methods, R, Python, Julia, Natural Language Processing, Bayesian Inference, Mathematical Modelling, Deep Learning, Data Analysis, Stakeholder Management, Scientific Review, Project Management

Industry

Government Administration

Description

We are currently looking for a Senior Data Scientist to join our Scientific Data & Insight Function within the Safety & Surveillance group. This is a full-time opportunity, on a permanent basis. The role will be based in 10 South Colonnade, Canary Wharf London, E14 4PU. Government departments and agencies are working towards implementing a minimum 60% attendance in office sites. We are currently implementing a flexible, hybrid way of working, with a minimum of 8 days per month working on site to enable the collaboration and contact with partners and stakeholders needed to deliver MHRA business. Attendance on site is driven by business needs so depending on the nature of the role, this can flex up to 12 days a month, with the remainder of time worked either remotely or in the office. Some roles will need to be on site more regularly. Who are we? The Medicines and Healthcare products Regulatory Agency enhance and improve the health of millions of people every day through the effective regulation of medicines and medical devices, underpinned by science and research. To deliver effectively on our central mission of protecting public health, we need robust vigilance processes that are able to quickly detect, monitor and evaluate safety signals across the product lifecycle, the ability to critically evaluate the benefit/risk balance of signals of concern and design effective risk mitigations, to communicate effectively to patients and the public and a healthcare system able to implement them. The Safety and Surveillance Group brings together into a single integrated structure expertise on the safety of all medical products with enforcement capabilities. These functions are supported by the Agency’s data and evidence generating capabilities complementing our signal generating abilities delivered via the common vigilance platform SafetyConnect. Safety remains at the heart of all our decision making across the product life cycle. The central mission of the Safety & Surveillance portfolio is to protect the public by appropriately identifying, assessing and managing the risks associated with medical products. In every aspect of this work, we harness the best science, technology, information and professional practice to protect patients in new and impactful ways. In support of this mission, the Scientific Data & Insight (SD&I) function is responsible for developing expertise in house to deliver evidence to underpin these new approaches. Quality and speed of regulatory decision making is dependent on having access to high-quality, representative data in a timely fashion but also being able to access and analyse in house data and information in the most effective way. A critical aspect of this work will include the exploration and application of new analytical methodologies including AI and machine learning methods such as natural language processing, large language models and computer modelling and simulation approaches. Hence developing and strengthening capacity and capability in data science within MHRA is a key strategic objective to ensure we are best placed to address the future evidence generation needs for both medicines and devices. What’s the role? The post holder is responsible for leading a team of data scientists. This involves developing innovative and novel analytical approaches, including state of the art machine learning, AI and simulation methods improve the agency’s activities in Safety and Surveillance. Key responsibilities: Line manage and lead a team of device data researchers and data scientists in applying analytical methods to patient data collated through vigilance systems to support assessment of the safety of medicines and medical devices and advise on the refinement of AI tools for data processing. Support the implementation of new analytical approaches to better interrogate incident reporting data, including the development of automated analytical approaches. Interact across the Agency and with external stakeholders to optimise device data quality, encouraging collaboration across areas. Working with vigilance scientists, developers, and epidemiologists to optimise vigilance reporting systems, including the application machine learning where appropriate. Who are we looking for? Our successful candidate will have the following: Leadership: Effectively lead and develop data scientists; promotes collaboration, knowledge sharing, and a results‑driven team environment. Experience in analysing and interpreting data from various sources to support decisions. Experience in leading a team of data scientists and achieving through others. Strong experience of using machine learning or data science to analyse and model large datasets. A PhD in Data Science, Statistics, Machine Learning, Computer Science or a similar quantitative discipline or demonstrable equivalent professional experience. Expertise in using programming tools such as R, Python, or Julia to characterise or analyse health data. Demonstrable technical knowledge and skills in at least one of the following domains: mathematical modelling and simulations, machine learning, deep learning, natural language processing, Bayesian inference. Person Specification: Method of assessment: A=Application, I=Interview, P=Presentation Behaviour Criteria: Seeing the big picture (A, I, P) Leadership (A, I, P) Communicating and Influencing (A, I, P) Experience Criteria: Experience of leading a team of machine learning scientists and achieving through others. (A, I, P) Strong experience of using machine learning or data science to analyse and model large datasets. (A, I, P) Strong experience of working collaboratively within multidisciplinary data science teams and delivering results in a timely way. (A, I, P) Demonstrable experience of communicating complex concepts and results effectively to a wide range of stakeholders. (A, I, P) Proven ability to independently produce well-focused scientific reviews and presentations. (A, I, P) Experience in writing grant proposals is desirable. (A, I, P) Experience of research using health related data sources and developing and implementing data analysis strategies. (A, I, P) Experience in leading projects to time demonstrating efficient and effective organisation and delivery skills. (A, I, P) Technical Criteria: A PhD in Data Science, Statistics, Machine Learning, Computer Science or a similar quantitative discipline or demonstrable equivalent professional experience. (A, I, P) Expertise in using programming tools such as R, Python, or Julia to characterise or analyse data, preferably health data. (A, I, P) Deep understanding of data science best practice. (A, I, P) Proficiency in scalable data analysis, for example using high performance computing. Demonstrable technical knowledge and skills in at least one of the following domains: Machine learning, deep learning, natural language processing, Bayesian inference. (A, I, P) Strengths Criteria Change Agent (I) Catalyst (I) Strategic (I) If you would like to find out more about this fantastic opportunity, please read our Job Description and Person Specification! Please note: The job description may not open in some internet browsers. Please use Chrome or Microsoft Edge. If you have any issue viewing the job description, please contact careers@mhra.gov.uk The selection process: We use the Civil Service Success Profiles to assess our candidates, find out more here. Online application form, including questions based on the Behaviour, Experience and Technical Success Profiles. Please ensure all application questions are completed in full; your application may not be considered if any responses are left blank. Our applications are CV blind, and our Hiring Managers will not be able to access your CV when reviewing your application. Presentation, to be prepared as part of your interview, with further information being supplied when you reach this stage. Interview, which can include questions based on the Behaviour, Experience, Technical and Strengths Success Profiles. In the instance that we receive a high number of applications, we will hold an initial sift based on the lead criteria of: PhD in Data Science, Statistics, Machine Learning, Computer Science or a similar quantitative discipline or demonstrable equivalent professional experience. Applicants are assessed on whether they meet any mandatory requirements as well as the necessary skills and experience for the role. Applications are scored based on the competency-based answers provided- ensure you have read these thoroughly and allow sufficient time. You can view the competencies for this role in the job description. Use of AI in Job Applications Artificial Intelligence can be a useful tool to support your application, however, all examples and statements provided must be truthful, factually accurate and taken directly from your own experience. Where plagiarism has been identified (presenting the ideas and experiences of others, or generated by artificial intelligence, as your own) applications may be withdrawn and internal candidates may be subject to disciplinary action. Please see our candidate guidance for more information on appropriate and inappropriate use. If you require any disability related adjustments at any point during the process, please contact careers@mhra.gov.uk as soon as possible. Closing date: 01 March 2026 Shortlisting date: From 02 March 2026 Interview date: 19 March 2026 If you need assistance applying for this role or have any other questions, please contact careers@mhra.gov.uk Candidates will be subject to UK immigration requirements as well as Civil Service nationality rules. Further information on whether you are able to apply is available here. Successful candidates must pass a disclosure and barring security check as well as animal rights and pro-life activism checks. People working with government assets must complete basic personnel security standard checks. Certain roles within the MHRA will require post holders to have vaccinations, and in some circumstances, routine health surveillance. These roles include: Laboratory-based roles working directly with known pathogens Maintenance roles, particularly those required to work in laboratory settings Roles that involve visiting other establishments where vaccination is required Roles required to travel overseas where specific vaccination may be required. Applicants who are successful at interview will be, as part of pre-employment screening subject to a check on the Internal Fraud Database (IFD). This check will provide information about employees who have been dismissed for fraud or dishonesty offences. This check also applies to employees who resign or otherwise leave before being dismissed for fraud or dishonesty had their employment continued. Any applicant’s details held on the IFD will be refused employment. A candidate is not eligible to apply for a role within the Civil Service if the application is made within a 5 year period following a dismissal for carrying out internal fraud against government. Any move to the MHRA from another employer will mean you can no longer access childcare vouchers. This includes moves between government departments. You may however be eligible for other government schemes, including Tax-Free Childcare. Determine your eligibility here. Individuals appointed on level transfer will retain their existing salary and are responsible for ensuring they fully understand the financial implications of any potential move and the impact (if any) on their terms. If an individual is in any doubt, they should seek clarification before accepting a job offer. Staff joining on promotion will receive up to a 10% increase of their current basic salary, or the pay band minimum, whichever is the greater. The individual will not retain any allowances paid by the former department/Agency, unless there are special circumstances, such as a reserved right to those allowances on transfer. Successful candidates may be subject to annual Occupational Health reviews dependent on role requirements. If you have any queries, please contact careers@mhra.gov.uk. In accordance with the Civil Service Commissioners’ Recruitment Principles our recruitment and selection processes are underpinned by the requirement of selection for appointment on the basis of merit by a fair and open competition. If you feel your application has not been treated in accordance with the Recruitment Principles and you wish to make a complaint, you should firstly contact careers@mhra.gov.uk If you are not satisfied with the response you receive, you can contact the Civil Service Commission at: civilservicecommission.independent.gov.uk info@csc.gov.uk Civil Service Commission Room G/8 1 Horse Guards Road London SW1A 2HQ About Us The Medicines and Healthcare products Regulatory Agency enhance and improve the health of millions of people every day through the effective regulation of medicines and medical devices, underpinned by science and research. The agency is made up of c.1300 staff working across two main centres and peripatetically across the UK and abroad. The agency consists of Corporate, Digital & Technology, Enablement, Healthcare Quality & Access, Partnerships, Safety & Surveillance and Scientific Research & Innovation.

Responsibilities

The post holder is responsible for leading a team of data scientists, developing innovative analytical approaches using state-of-the-art machine learning, AI, and simulation methods to improve Safety and Surveillance activities. Key duties include line managing researchers and scientists, applying analytical methods to patient data, and supporting the implementation of new automated analytical approaches.