Data Scientist - £46,160 - £51,666 p.a. + benefits

Job summary

We are currently looking for Data Scientists x2 to join our Scientific Data & Insight Functionwithin the Safety & Surveillance group.

One full-time permanent opportunity and one full-time12 month fixed term contract, internal move, loan or temporary promotion available. These roles will be based in 10 South Colonnade, Canary Wharf London, E14 4PU.

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 6 groups – Corporate, Partnerships, Scientific Research & Innovation, Healthcare Quality & Access, Safety & Surveillance, and Digital & Technology.

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.

Job description

The Agency is facing a rapidly evolving external environment involving increasingly complex products and utilisation of these products across an ever more diverse health system. The post holder will have data science expertise to support and develop world-leading vigilance systems designed to gather, collate, and analyse data relevant to the safety of medicines, vaccines, and medical devices.

The post holder is responsible for using data science techniques to design and develop innovative and novel analytical approaches to interrogate datasets and generate evidence which is relevant for regulatory decision making. The post holder will ensure access to real world data in a timely fashion for regulatory needs and develop analytical approaches to make business activities more effective.

The post holder will work closely with other members of the Scientific Data & Insight function and regularly interact with colleagues across the Safety & Surveillance Group, including the Clinical Practice Research Datalink, and wider Agency.

Key responsibilities

• Apply data science and machine learning approaches to large and complex datasets using programming languages such as Python, R, or Julia to generate actionable insights and robust evidence.
• Communicate approaches and results clearly and effectively to a wide range of stakeholders, including using data visualisation methods.
• Produce data science solutions that are robust, reproducible, and scalable by applying technical best practices.
• Work cross-functionally to enable the delivery of innovative evidence-generation and collaborate with external partners to enable data-driven discovery in medical product safety.
• Apply 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.
• Work with vigilance scientists, developers, and epidemiologists to design and optimise vigilance reporting systems, including the application machine learning where appropriate.
• Evaluate and optimize data quality, ensure that data science solutions are fit-for-purpose and appropriately maintained, and provide quality assurance where appropriate.
• Engage with a wide range of stakeholders to facilitate their use of vigilance tools.
• Support the development of grant proposals and the delivery of a sustainable operating model.
• Become a rapid expert in unfamiliar areas for driving operational research across the organization.
• Ideate and propose new research ideas based on novel technologies identified in horizon scanning such as literature reviews or conferences.

The job description is not intended to be exhaustive, and it is likely that duties may be altered from time to time in the light of changing circumstances and after consultation with the postholder.

Person specification

Essential Criteria:

• Strong experience of using machine learning or data science to analyse and model large datasets.
• Experience in developing clear, effective, and reproducible code through data science best practices.
• Experience of data visualisation and presentation of complex information.
• Experience of working collaboratively within multidisciplinary data science teams and delivering results in a timely way.
• Experience of communicating complex data science concepts and results effectively to a wide range of stakeholders.
• Interest in applying advanced analytical methods to support the safety of medicines, vaccines and medical devices
• A PhD in Data Science, Statistics, Machine Learning, Computer Science or a similar quantitative discipline or demonstrable equivalent professional experience (Lead).
• Proficiency in programming languages such as Python, R, or Julia.
• Understanding of data science best practice.
• Proficiency in scalable data analysis, for example using high performance computing.
• 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.

Candidates need to be members of the Government Operational Research profession or meet the membership criteria for the Operational Research profession (numerate degree at 2.1 or significant experience with quantitative analysis). Where candidates who are not members will undergo a standard badging assessment for the Government analytical profession at interview. The postholder must demonstrate in their CV that they meet the minimum requirements for badging.

We'll assess you against these professional skills during the selection process:

• Knowledge and application of OR skills and techniques

• Achieving impact with analysis

For more information, please see -