As a Data Engineer/Wrangler in epidemiology you will clean, transform and integrate complex, multi-source data from large-scale epidemiological and real-word data. Your work will ensure data readiness for research, in collaboration with a multidisciplinary team of epidemiologists, statisticians, data scientists and data managers. This is an exciting opportunity to play a crucial role in the creation of end-to-end data management and processing solutions, according to FAIR (Findable, Accessible, Interoperable and Re-usable) principles to support efficient and secure research data re-use to advance science. You will work with the Integrative Epidemiology Team (led by Professor Montserrat Garcia- Closas) and Clinical Epidemiology Team (led by Professor Amy Berrington) at the ICR Division of Genetics and Epidemiology, to join our dynamic and forefront research group using epidemiological and real-world data-driven approaches to understand the causes of cancer and how to prevent it.

Key Requirements

The successful candidate must have a Master’s degree in epidemiology, biostatistics, or data science and proven experience in data engineering/wrangling, or data management, ideally with large, complex datasets in biomedical, epidemiological, or public health contexts.

Department/Directorate Information

At the ICR Division of Genetics and Epidemiology, the Integrative Epidemiology Team uses integrative analyses of large-scale data in epidemiological studies to investigate the causes of cancer, understand carcinogenic processes and improve risk assessment for precision prevention. The Clinical Epidemiology Team uses real world data to investigate the late-effects of cancer treatments, cancer survival and cancer risks from other medications. Our work informs prevention and public health strategies at both the population and individual levels to reduce the burden of cancer.

We have a program of research based on the ongoing Generations Study, a national study of over 110,000 women from the UK. Data includes self- reported risk factor information, hormone levels, genetics, and artificial intelligence (AI) analyses of tissue images from breast tumours, benign breast disease and mammography images. We also access their medical records to collect information on cancer screening and treatments. The scientific staff comprise epidemiologists, statisticians and data scientist who collaborate with researchers around the world. We are part of the newly formed Cancer Epidemiology and Prevention Research Unit and collaborations/strategic-collaborations/the-cancer-epidemiology- and-prevention-research-unit-(cepru), a research partnership between The ICR and Imperial College London to establish collaborations in research, training and knowledge dissemination in cancer epidemiology and prevention.