Sam's area of research is in using machine learning and natural language processing to answer questions about adult social care. He uses programming tools 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 qualification in Data Science from Johns Hopkins School of Public Health, which encompasses 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 adult social 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 prior to this 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, such as the European Project Data Explorer and Visualising Discharges. Sam has published research in the British Journal of Social Work and BMJ Open.