Adigens Health is growing! Looking for an Associate RWE Scientist / RWE Scientist.

Job Title: Associate RWE Scientist / RWE Scientist

Location: Ireland

Type: Full-Time/Part-Time

Start Date: ASAP

About Us

We are a scientific and analytical company dedicated to providing strategic and scientific/research support to life science companies. Our mission is to tackle complex challenges with tailored solutions that enable our clients to innovate and thrive in the rapidly evolving healthcare landscape.

As a growing company, we are looking for a Master’s-level Associate RWE Scientist or RWE Scientist. The position will be based in Ireland.

The ideal candidate will have a strong foundation in epidemiological methods, data analysis, and healthcare datasets, along with the ability to work in a fast-paced environment. You will support strategic initiatives, conduct quantitative analyses, and contribute to research projects that shape decision-making for biotech, pharmaceutical, and healthcare organisations.

1. Purpose of the Role

The Employee will perform epidemiological research and project activities using real-world healthcare data to support client programmes. The role focuses on study design and the application of epidemiological methods, with opportunities to develop expertise in causal inference and target trial emulation through project work and mentorship. The Employee will contribute to projects under the guidance of senior staff, taking on increasing responsibility for methodological components as experience grows.

2. Key Duties and Responsibilities

2.1 Study Design and Methods (as assigned)

•        Contribute to the design of observational studies under the guidance of senior staff, including defining research questions, estimands and estimators.

•        Support the specification of target trials and the design of their emulation with real-world data, such as electronic health records and administrative claims.

•        Help identify potential sources of bias (e.g., confounding, selection bias, immortal time) and the design features that address them.

•        Develop familiarity with causal-inference methods (e.g., target trial emulation, propensity score methods, g-methods) through project exposure and mentorship.

•        Apply appropriate epidemiologic methods (e.g., descriptive epidemiology, burden of illness, treatment patterns) under guidance from senior staff.

•        Contribute to evaluating the fitness-for-purpose of real-world data sources.

•        Assist in drafting and amending study protocols and statistical analysis plans (SAPs), with increasing independence over time.

•        Review and summarise the published literature to inform study design, and contribute to the methodological appraisal of published studies and client materials under senior guidance.

•        Develop familiarity with regulatory and HTA expectations for real-world evidence (e.g., FDA, EMA, NICE) and with reporting guidelines (e.g., STROBE, TARGET).

2.2 Project Execution and Coordination

•        Support day-to-day delivery of defined projects, including tracking timelines, actions, and dependencies.

•        Contribute to timely, accurate deliverables: protocol and SAP sections, literature summaries, slide decks, and technical appendices.

2.3 Client and Internal Collaboration

•        Participate in client meetings; capture requirements and action items, and help communicate implications for scope, timelines, and study design.

•        Share knowledge across the wider team and take part in internal methods training.

•        Contribute to internal methods notes, templates, and reusable deliverables.

•        Support the preparation of training materials and workshops for clients and internal teams.

3. Skills and Qualifications

•        Master's degree in Epidemiology, Biostatistics or a closely related field.

•        Strong interest in epidemiological methods and observational study design.

•        Training or experience in causal inference (e.g., target trial emulation, g-methods, propensity score methods) is an advantage.

•        Familiarity with real-world data sources (e.g., registries, electronic health records, administrative claims) is an advantage.

•        Familiarity with statistical programming (e.g., R, SAS, Stata) is an advantage.

•        Strong written and verbal communication skills; comfortable operating in a fast-paced, client-facing environment and asking clarifying questions in meetings.

How to Apply

If this sounds like the right opportunity for you, please send your CV and a brief cover letter to info@adigenshealth.com.