Data Science Lead: Sponsorship Available

Job summary

West and North London Integrated Care Board (WNL ICB) are recruiting a Lead Data Scientist to build out our in-house data science capability at an exciting time in our development. Through our investment in One London, we hold linked, person-level data spanning primary care, hospitals, mental health, community and social care for our population, a rich asset to model from. We’ve recently migrated our analytics platform to Snowflake, so you’ll be shaping a modern, cloud-native stack from an early stage.

As an experienced technical leader and researcher, you’ll use advanced predictive and prescriptive methods (causal inference, stochastic simulation, Bayesian hierarchical modelling, machine learning and more) to tackle real strategic and operational questions, e.g., forecasting the financial and population health impact of a new service before it launches, building risk models to identify who could benefit from proactive care, simulating the impact of a business case before money is committed, and evaluating whether the care models we’ve introduced are actually working. You’ll productionise these into tools used across the WNL health and care system, impacting real-world strategic, operational and clinical decision-making. You’ll play a key role in ensuring these new data and technologies are used responsibly and ethically to ensure this innovation does not perpetuate existing health inequalities and must feel confident promoting these principles.

Main duties of the job

• Independently delivering end-to-end data science projects yielding actionable insights and tools in production that enable users to tackle real-world strategic and operational problems. Considering user needs, data quality and management, user experience and engagement, deployment, and making best use of statistical and machine learning methods.

• Rigorously applying appropriate advanced statistical and data science methodologies to generate robust and reliable insights communicated with appropriate levels of uncertainty

• Maintaining knowledge of a broad range of advanced statistical methodologies to identify and apply the most appropriate technical solution to a given problem, alongside a modelling specialism in line with the seniority of the role

• Advanced use of open-source analytical tools (including R or Python) to develop and deploy (Snowflake, Docker, Github Actions) models and applications, and to assess and monitor model outputs

• Set technical standards, actively contribute to high-level architectural decisions and identify development opportunities for yourself and those around you and adopt innovative practices learned from the wider analytics community

• Matrix management and coaching of senior data scientists to deliver advanced models and productionise tool.

Person Specification

Education/ Knowledge and Qualifications

Essential

• Educated to Master level / equivalent experience in Data/analytics field
• Evidence of post qualifying and continuing professional development
• Demonstrable knowledge in relevant analytical fields, their associated methods, and their potential for application within healthcare, including advanced statistics, epidemiology, data science, econometrics, and operational research
• Expert knowledge of the role of analysis in improving decision quality and be capable of supporting advanced decision-making methods (e.g. multicriteria decision analysis)
• Expert understanding of advanced analytical methods, including a specialism of one or more of machine learning, simulation or, causal inference. Knowledge covers modelling, best practices in training, deployment, monitoring and ethics
• An understanding of the aims of current healthcare policy in London, including the background of the policy and its implications

Desirable

• Educated to PhD level or equivalent level of experience of working in an industry role applying data science methods
• An active member of relevant professional body and/or wider analytical networks.
• Good understanding of the principles of data engineering best practices

Expierence

Essential

• Track record of independently leading work with system leaders to influence decision making and translate analytics projects into real world system wide transformation
• Demonstrated experience several of the following with at least one specialism: Simulation methods, such as Discrete Event Simulation, System Dynamics, and MCMC. Regression modelling, generalised linear models such as logistic or Poisson, multilevel models, Analysis of Variance. Bayesian approaches to modelling Causal inference Epidemiology Machine Learning / predictive models: regression/classification trees, random forests, boosting, neural networks Experimental design and applying the appropriate testing framework to analytics. Observational study design using real world data
• Expert in open-source scripting languages, such as Python/ R
• Expert in the using the tools of reproducible analytic pipelines, such as git, GitHub, package development, documentation, automation, and code review
• Experience working with real world data routinely collected from operational systems such as Electronic Patient Records (EPRs
• Experience supporting team members to develop professionally
• Experience of managing projects using project principles techniques and tools such as Prince 2, CRISP-DM and agile
• Experience delivering automated operational tools such as automating manual reporting processes or deploying models or applications in production

Desirable

• Experience of orchestrating and quality assuring data pipelines on a cloud platform (e.g., DBT in Snowflake)
• Experience of model deployment and associated tools
• Experience of model monitoring methods and associated tools

Skills and Abilities

Essential

• Expert knowledge of predictive, prescriptive and/or evaluative analytical techniques
• Expert in delivering actionable insights using static and/or interactive data visualisation where appropriate
• Able to scope several solutions to a business problem and triage to propose the most appropriate solution within the operational constraints and resolution needed to make a decision
• Proven skills in working collaboratively across organisations and managing conflicting expectations
• Evidence of delivering results through others using a range of levers in the absence of direct line management responsibility
• Problem solving skills and ability to respond to sudden unexpected demands

Desirable

• Knowledge of information governance and clinical assurance processes required to use NHS data in PHM products

Communication

Essential

• Ability to explain the principles, results, implications, strengths and limitations of analytical methods to technical and non-technical audiences
• Provide and receive highly complex, sensitive and contentious information, negotiate with senior stakeholders on difficult and controversial issues, and present complex and sensitive information to large and influential groups.
• Persuade team members and stakeholders of the respective merits of different options, innovation and new tech opportunities.
• Able to communicate findings and clear actionable insights to non-analyst colleagues

Effort factors

Essential

• Capable of managing own workload and making informed decisions in the absence of required information, working to tight and often changing timescales
• Proactively identifies areas for professional development and able to independently learn technical skills
• Able to make decisions autonomously when required and appropriate

Values and Behaviours

Essential

• Commitment to the values and principles of system working agreed across the ICB footprint
• Ability to actively promote equality, diversity and inclusion within all areas of responsibility
• Demonstrates a strong desire to improve outcomes and make a difference by focusing on goals.

Closing Date: 27 September 2026