At Sensyne Health we combine technology and ethically sourced patient data to help people everywhere get better care. To do this, we have created a unique partnership with the NHS that delivers a return to our partner Trusts and unlocks the value of clinical data for research while safeguarding patient privacy. Alongside this, we develop clinically validated software applications that create clinician and patient benefit while providing highly curated data. Our products include vital-signs monitoring in hospitals and patient-to-clinician apps to support self-care and remote monitoring of gestational diabetes and chronic diseases such as COPD and heart failure.
Our Intelligent Systems Medicine team is currently expanding to bring further expertise into a cross functional environment. The aim is to drive the next generation of innovation for better patient outcomes, whilst harnessing some of the industry’s most progressive AI approaches. This is centred on data-efficient machine learning algorithms. The nature of our team is collaborative with an emphasis on genuine passion for healthcare advancement. The roles are research based with high potential for professional growth, support towards our business goal and ongoing contribution to the development of healthcare by working in a stimulating environment focused on improving patient outcomes.We use our proprietary clinical AI technology to analyse ethically sourced, clinically curated, anonymised patient data to solve serious unmet medical needs across a wide range of therapeutic areas, enabling a new approach to clinical trial design, drug discovery, development and post-marketing surveillance.
We are seeking an experienced Medical Statistician with a strong background in statistical modelling (e.g., longitudinal data analysis, generalised linear mixed models, multinomial models, etc.) for large-scale data analytics and predictive modelling. The Medical Statistician needs to be familiar with statistical programming languages (e.g., R, Python). The main responsibilities of the role include data management and cleaning, data integration, and constructing advanced statistical models to address important questions about risk factors for diseases from databases including data from several hundred thousand individuals.
The Medical Statistician will work closely with a wider team of machine learning researchers bioinformaticians, computational biologists, programmers and clinical researchers within the Intelligent Systems Medicine Department. The successful candidate will provide statistical expertise, and will be actively involved in study design, data preparation and analyses, preparation of reports and presentation of research.
- Preparing statistical analysis plans, undertaking statistical analyses, and taking full responsibility for data analyses.
- Recognising problems arising during the execution and analysis of studies and identifying possible solutions.
- Identifying data to be collected, developing coding schedules. Extracting and manipulating subsets of the data for use in research projects.
- Central management (including, but not limited to design, development, linkage, cleaning, validating, consistency checking and refining) of multiple large databases.
- Preparing data dumps, managing data, performing data cleaning, and providing advice on data preparation.
- Writing relevant sections of any report/paper/presentation, including preparation of graphics for public presentations.
- Present findings at internal meetings
- A postgraduate degree in statistics (or closely related subjects)
- Experience in advanced statistical modelling including longitudinal data analysis and mixed model.
- Experience or interest in using statistical modelling to prepare clinical trials and analyse their outcome.
- Experience in R or Python
- Experience in conducting analysis of medical research data.
- Independence and initiative to work unsupervised with excellent attention to detail.
- Interest in medical research (e.g. epidemiology, public health)
- Cross-disciplinary problem-solving and project-management skills.
- Ability to assimilate current statistical and mathematical literature on a topic and address investigations accordingly.
- Excellent time management and organizational skills.
- Experience or interest in multivariate survival analysis and causal inference
- Experience theoretical derivation of hoc statistical models
- Familiarity with database languages; e.g. SQL.
- Experience of data management at large scale.
- Documenting, maintaining and organizing well-structured versions of the database schemas and data dictionaries.
- Experience in genetic analysis e.g. GWAS.
- Experience in mathematical modelling.
- Exploring IT and data management tools for handling large and complex datasets, in particular in relation to future genome-wide association.
- Company share option scheme
- 5% employer matched Pension scheme
- BUPA Health Insurance including Partners and Children cover
- Free Gym Membership
- Cycle to work scheme
- A challenging and fun environment that rewards results