Care Policy and Evaluation Centre, London School of Economics and Political Science
Sam currently works as a Research Officer in Data Science and the Care System in the Care Policy Evaluation Centre (CPEC) at the London School of Economics and Political Science (LSE). Sam’s research use machine learning and natural language processing to answer questions about long term care. He uses programming languages like R and Python to extract information from care data to evaluate care interventions.
Sam has an MA (Cantab) in Social and Political Science, an MA (with distinction) in Social Work from Goldsmiths College, and a Data Science certification from Johns Hopkins School of Public Health encompassing R programming, regression modelling, and machine learning. While working at CPEC, he is completing a PhD by papers focusing on using unstructured text data to improve long term care policy and operations.
Prior to working at CPEC, Sam gained experience in adult social care operations in inner London, managing a local authority social services team, and as a qualified social worker. He has over ten years’ experience managing and working in adult social care services in hospitals and the community. Sam has worked in user-facing services for adults with a range of needs, including dementia, physical disabilities and long-term conditions, learning disabilities, mental health issues, drug and alcohol issues, and adults with a history of offending.
Sam also enjoys using and creating interactive products that can increase public and professional understanding of research.
|Topics||Community-based LTC; Data catalogues; Financing LTC; LTC Policy; LTC Systems; Technology and LTC;|
|Methods||Causal inference in Long-Term Care; Data science and LTC research; Economic evaluation; Quantitative data analysis;|
|Interest Groups||Data Science;|
Computational natural language processing; administrative care records; web scraping; APIs; machine learning; geospatial methods; regression modelling; data visualisation.