Postdoctoral Statistician — CYP Health Analytics


Company:	NHS Jobs
Salary:	£49,387 - £56,515
Hours:	Full-time
Location:	Cambridge, CB2 0SZ
Job type:	Contract
Posting date:	20 Aug 2026
Closing date:	2 Sept 2026

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Summary

Please refer to the attached job description and person specification for full details of responsibilities. Working with data prepared and quality-assured by the CADRE data engineering team, the postholder will contribute to longitudinal analyses of the cohort, including: Describing the cohort at index event (first contact with health, education, or social care services), including individual characteristics, service type, assessment outcomes, diagnoses, and severity measures. Estimating the prevalence and incidence of diagnoses and identified needs longitudinally, and examining how these differ across health and care settings. Conducting time-to-event analyses examining delays to diagnosis or treatment following initial presentation. Measuring candidate risk and protective factors, exploring sub-group structure and clustering. Exploring relationships between variables and carrying out feature engineering steps required to support predictive modelling.The postholder will develop and validate predictive models aimed at: Modelling future risk of mental health problems in CYP prior to contact with mental health or social care services. Identifying early signs of existing mental health problems within routinely collected multi-agency data. Exploring optimal intervention matching based on identified need profiles. Comparing and evaluating traditional statistical approaches (e.g. multi-level regression, generalised linear models, survival analysis) alongside machine learning and AI methods, selecting approaches appropriate to the research question and data structure. Prepare high-quality manuscripts for peer-reviewed publication across statistical, clinical, and public health journals. Contributing to the development of a validated risk stratification tool suitable for integration into clinical pathways and for use as an enrichment strategy for randomised controlled trials.

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