OverviewDirect message the job poster from Opus Recruitment SolutionsI'm currently supporting a company that has adopted OMOP/OHDSI as a systematic and standardized approach to real-world evidence (RWE). Data are converted into the OMOP Common Data Model, making queries and analytics interoperable and sharable. In addition, the generation of these queries and tools and its execution can be separated, both physically as well as logically, creating the opportunity to develop code for purposes of descriptive statistics or hypothesis testing in the absence of a direct data access to all data assets being targeted. As a consequence, our team can generate insights across multiple datasets in our collaborators network.The Data Standardization & Analytics team's mission is to deliver world class and globally scalable projects through:

Rapid analytics - to assess study feasibility and availability of data Characterization of patient populations: their demographics, the distribution of their comorbidities, the duration between diagnosis and intervention, treatment patterns etc. Protocol-driven analytics - estimating the association between clinical interventions and their outcomes – benefits and adverse events. Predictive models for determination of populations (phenotypes) or outcomes (patient-level predictions). Network studies – co-ordinating the execution of RWE analytics across multiple external data partner sites. This requires global leadership across technical and data architecture, data manipulation, analytics script and report generation. The solutions are delivered to a variety of clients across life-science, government, payer or provider organizations. The team also curates the largest collection de-identified Real-World Data in the world in OMOP Common Data Model, from different patient care settings in multiple countries worldwide, making it the forefront of “Big Data” in healthcare. In this role you can expect to;

Design & develop analytical packages in R & SQL to extract real-world evidence from OMOP healthcare databases. Translate detailed research specifications into documented instructions, debug routine queries and prepares necessary documentation Contribute to client consultation on study ideation, study design and results interpretation. Executing retrospective analytical packages as part of OHDSI and other OMOP-based network initiatives. Work collaboratively with OMOP data scientists, plus other team members across DSAE. Support the Senior Data Scientists and other technical experts with building the team’s subject matter expertise with regards to the OMOP common data model. Collaborate with members of the OHDSI community, participate in the OHDSI community through study projects such as study-a-thons, code development and knowledge sharing Support customer focused training sessions and tutorials where necessary Our ideal candidate will have;Essential (candidate must have these)

Analytical / quantitative research background (preference for big data) Very nice to have (successful candidate will likely have several or all of these skills).

Pharmaco-epidemiology or RWE background (or relevant clinical or life science experience). Masters or PhD in a relevant quantitative field. OMOP experience. SQL programming. Consulting experience. AI /ML experience. Location and travel

Minimal travel expected to other offices (London, East Coast US) or to attend conferences and workshops as required. Home-based If you're ready for a new and exciting opportunity with an industry leader in the healthcare industry, click apply and we'll be in touch! Seniority levelMid-Senior levelEmployment typeFull-timeJob functionInformation TechnologyIndustriesHospitals and Health Care #J-18808-Ljbffr