Senior Data Scientist
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About us
We are a leading consultancy with a purpose to make an enduring impact on health and healthcare. We work with leaders and frontline teams to improve health, transform healthcare, drive adoption of innovation and create value through investment.
Our consultancy serves the entire healthcare sector, from payors and providers of care, to life science companies, health tech and sector suppliers and health investors. We provide end-to-end services, from strategy through implementation, accelerated by data, digital and AI.
We shape opinion through evidence-based thought leadership on key issues affecting health. With unmatched ability to access and use health data, our consultants are a driving force for delivering positive and meaningful change.
Our strategic intent
We are focused on building the leading consulting company dedicated to health. We serve the entire healthcare sector, including healthcare systems (providers, payors and regulators), life sciences (pharmaceuticals, biotech, devices and diagnostics), health technology, health investors, and the wider supplier landscape.
We provide end-to-end services, from strategy through implementation, supporting organisations to improve population health and healthcare outcomes. Our work spans strategy and transformation, finance and performance improvement, and delivery accelerated by data, digital and AI. We help clients understand their ambitions, identify opportunities to create value, apply innovation in practice, and deliver sustainable, measurable change.
Our Mission
Our mission is to be invaluable to our clients, supporting them to innovate and make lasting improvements and to build an exceptional company that attracts, develops, and retains a trusted and uniquely talented team.
About the role
The Senior Data Scientist is a senior technical contributor within CF’s Data Innovation team, playing a critical role in the design and delivery of high-impact data science solutions across the healthcare sector. The role sits at the intersection of advanced analytics, healthcare strategy, and client delivery, supporting NHS, life sciences, and health sector clients to improve outcomes, inform decision-making, and create value through data.
Senior Data Scientists work closely with consultants, clients, and other technical specialists to scope, shape, and deliver complex analytical work. They are comfortable operating in ambiguous problem spaces, applying structured problem-solving and strong technical judgement to translate complex business, clinical, and policy questions into robust, actionable analytics.
The role focuses on hands-on delivery excellence, technical oversight within projects, and high-quality client engagement. Senior Data Scientists contribute to the development of CF’s data capabilities and ways of working, while supporting and mentoring junior colleagues.
Responsibilities
Delivery
- Partner with NHS, life sciences, and other healthcare clients to translate complex and ambiguous questions into well-defined analytical problem statements
- Lead the end-to-end delivery of data science workstreams, from scoping and design through to analysis, insight generation, and client presentation
- Act as a trusted analytical advisor within projects, shaping both the analytical approach and the resulting solution
Advanced analytics and modelling
- Design and develop predictive models to forecast health outcomes, healthcare utilisation, and medicine sales performance
- Conduct population health analyses, disease burden studies, and real-world evidence (RWE) research using large-scale healthcare datasets
- Apply robust statistical methods to ensure analytical rigour, transparency, and interpretability
- Extract insight from both structured and unstructured data sources, including clinical text and public data
- Ensure analytical outputs are decision-focused and aligned to client objectives
Data engineering and pipelines
- Design, build, and maintain complex data pipelines integrating multiple disparate data sources
- Ensure data quality, reliability, security, and scalability across analytical solutions
- Apply software engineering best practices to data workflows to support reuse, testing, and long-term maintainability
Software engineering and reproducibility
- Write clean, well-structured, reproducible Python code with clear documentation
- Implement unit tests, data validation checks, and quality controls
- Contribute to CI/CD pipelines for analytics and data workflows
- Use Git effectively, including collaborative development, version control, and code reviews
- Manage Python environments using tools such as conda, uv, poetry, pip, or equivalent
- Use Bash and cloud tooling (e.g. AWS CLI) for automation and orchestration
- Build solutions that are production-minded, not purely exploratory
Stakeholder and delivery management
- Lead technical discussions, workshops, and presentations with client stakeholders
- Proactively identify risks, dependencies, and delivery constraints within data workstreams
- Maintain high standards of documentation, reproducibility, and delivery excellence
- Support integrated working between data science and consulting teams
Requirements
We are ideally seeking candidates with a combination of the following skills and experiences:
Mandatory
- Degree or postgraduate qualification in a relevant field (e.g. Data Science, Computer Science, Statistics, Mathematics)
- Strong experience delivering data science projects in a consulting or project-based environment
- Advanced Python and SQL skills for data manipulation, analysis, and modelling
- Strong experience with Git and collaborative development workflows
- Comfortable working with Bash and command-line tooling
- Experience managing Python environments using conda, uv, poetry, pip, or similar
- Experience working with cloud-based data storage solutions (e.g. AWS or GCP), with understanding of security, encryption, and access management
- Proven experience designing and implementing complex data pipelines
- Strong grounding in statistics and applied analytics, including regression, hypothesis testing, time series, and predictive modelling
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical audiences
Desirable
- Experience working with healthcare or pharmaceutical data
- Knowledge of population health, epidemiology, health economics, or real-world evidence methodologies
- Experience forecasting healthcare demand, utilisation, or commercial performance in life sciences
- Familiarity with healthcare data standards, coding systems, or clinical pathways
- Experience working with unstructured data, NLP, or advanced machine learning techniques
Flexible working
Our default is to work in person with our clients, but we also support remote working. Team members can work from home one day per week as standard, and we offer an additional 44 remote working days per year. This allows you to work from home up to two days per week-subject to client needs- or use your allowance in blocks, depending on what works best for you. Office hours are flexible within our core hours of 10am–4pm.
Benefits
- We offer a competitive and flexible reward package designed to support you at work and beyond it. You will benefit from a generous holiday allowance that grows with your career (minimum of 25 days), a strong employer pension contribution, and the freedom to tailor benefits to suit your lifestyle, from wellbeing and fitness to financial protection.