Data Scientist - Healthcare & RWE - OMOP
Listed on 2026-10-16
-
IT/Tech
Data Scientist, AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Analyst
Applied Data Scientist – Healthcare & RWE - OMOP
Location: UK, Remote
Permanent
We’re looking for a Applied Data Scientist with OMOP experience to join a growing health data and Real-World Evidence organisation, using AI and Generative AI alongside advanced data engineering to unlock insight from complex healthcare data.
Sitting at the intersection of Data Engineering, Data Science, AI and Healthcare Informatics
, you'll work with large, heterogeneous and often unstructured datasets, building solutions that support real-world evidence and observational research.
A key part of the role will be exploring and applying Generative AI technologies, including LLMs and Retrieval-Augmented Generation (RAG), to solve real research and healthcare data challenges.
What you'll be doing- Develop and apply AI and GenAI solutions
, including LLMs and RAG
, within healthcare research workflows - Work with vector databases
, retrieval techniques and unstructured data - Build and deliver analytics-ready Common Data Models (CDMs)
- Develop data models and pipelines across structured, semi-structured and unstructured healthcare data
- Work extensively with OMOP/OHDSI and healthcare data standards
- Explore graph-based data modelling, ontology mapping and entity resolution
- Act as a key bridge between Engineering and Data Science
- Partner with researchers and clinical stakeholders supporting RWE and observational research
- Build dashboards and visualisations to communicate research findings
- Work directly with customers to turn complex research questions into practical technical solutions
You’ll have strong SQL skills alongside Python and/or R, with experience working with complex real-world datasets.
With experience in following:
- Data modelling, database engineering and pipeline development
- OMOP, OHDSI, FHIR or similar healthcare data standards
- Real-World Data /
Real-World Evidence (RWD/RWE) - AI and GenAI solutions
, including LLMs and RAG - Healthcare, oncology, cancer research or wider Life Sciences data
- Graph technologies, ontologies or entity resolution
We're particularly interested in people who enjoy building rather than simply using existing tools – someone who can experiment with emerging AI technologies, understand where GenAI can genuinely add value, and turn ideas into robust solutions.
This could suit someone currently working as a Research Data Engineer, Applied Data Scientist, AI/Data Engineer, GenAI Engineer, Healthcare Data Scientist or RWE Data Scientist
.
Interested?
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