1051-Senior Data Scientist/Data Analyst – Real-World Data(RWD)-REMOTE in Ireland

Are you interested in working directly for a single sponsor while having the security and additional career opportunities that working for a global CRO can bring? Our team says it’s the best of both worlds….

ClinChoice is searching for a Senior Data Scientist/Data Analyst Consultant to join us.

ClinChoice is a global full-service CRO with a strong focus on quality, professional development, and supportive culture. As a client-facing role, we are looking for confident candidates with the ability to work independently whilst establishing a high-trust environment with the client’s counterparts.  

Main Job Tasks and Responsibilities: 

The Senior Data Scientist/Analyst will lead and execute complex analyses using Real-World Data (RWD) across multiple therapeutic areas. This individual will play a critical role in study design, protocol development, and advanced analytics to inform clinical, epidemiological, and health economics research strategies. The ideal candidate brings both deep technical expertise and a strategic mindset to collaborative, cross-functional research environments.

Key Responsibilities: 

Real-World Data Analysis & Study Leadership
•    Lead the design, implementation, and interpretation of complex RWD studies (e.g., cohort studies, safety analyses, feasibility assessments).
•    Contribute to and review study protocols and Statistical Analysis Plans (SAP) alongside epidemiologists and cross-functional partners.
•    Provide strategic input to ensure that study designs align with business goals and are analytically sound, given available data sources.
•    Execute analyses using large-scale RWD (claims, charge master, EHR) with R or SAS; lead development of Tables, Figures, and Listings (TFLs).
•    Present findings to scientific, clinical, and business stakeholders with clear interpretation of results and strategic recommendations.
•    Serve as a senior analytics representative on cross-functional study teams and act as a point-of-contact for analytics-related queries.
Oversight, Quality, and Communication
•     Oversee the programming and quality control of analytic deliverables; ensure reproducibility, transparency, and proper archiving.
•    Conduct or oversee QC of outputs generated by junior analysts or peers, as requested by Therapeutic Area (TA) Leads.
•    Provide regular updates to TA Analytics Leads and senior stakeholders on project progress, data issues, and prioritization.
Cross-Functional Analytical Support
Support broader enterprise needs across the following specialized areas:

A. Health Economics & Outcomes Research (HEOR) / PRO
•    Conduct and oversee HEOR analyses, including cost-of-illness, burden studies, comparative effectiveness research.
•    Work with stakeholders to incorporate patient-reported outcomes (PRO) and economic endpoints into RWE strategies.
•    Leverage SAS and SQL for data processing and HEOR model development.

B. OMOP CDM / OHDSI Analytics
•    Lead or support studies using OMOP CDM data and OHDSI tools, ensuring adherence to data standards and methodological rigor.
•    Translate research questions into OHDSI-compatible analyses using ATLAS, R packages, and custom tooling.
•    Contribute to the customization of OHDSI applications and address technical issues through collaboration with engineering teams.
•    Lead or participate in multi-database network studies using U.S. and ex-U.S. RWD assets.

C. Methods & Innovation
•    Co-develop advanced methodological research in partnership with epidemiology, safety, and biostatistics teams.
•    Design, validate, and refine phenotype algorithms for RWD-based studies.
•    Build cohorts and analytic pipelines to address key methodological challenges using claims and EHR data.
•    Coauthor scientific abstracts, posters, and manuscripts for peer-reviewed publication.

Education and Experience:

•    Advanced degree required: PhD or Master’s in Biostatistics, Epidemiology, Health Economics, Data Science, Computer Science, Public Health, or a related quantitative discipline.
•    Minimum 6–8 years of hands-on experience in RWD analysis, epidemiology, or health economics research in a pharmaceutical, academic, or consulting setting.
•    Proven expertise in R, SAS, and/or SQL for data processing and statistical modeling.
•    Experience with claims, EHR, or other healthcare databases, including knowledge of the OMOP CDM framework and OHDSI tool