Data Scientist - Medical Affairs Domain

Data Scientist (Medical Affairs / Real-World Evidence)

Experience Required: 5+ Years

Role Overview:

We are seeking an experienced Data Scientist to support evidence generation within the Medical Affairs team. The role involves working extensively with Real-World Data (RWD), clinical datasets, and HTA-related requirements to develop analytical insights and advanced R-Shiny applications that enable scientific storytelling, decision-making, and compliance with EU JCA and similar frameworks.

Key Responsibilities:

- Work with Real-World Data (RWD), HTA datasets, and clinical trial data to generate high-quality scientific evidence.

- Develop complex R-Shiny applications, including dynamic dashboards, animations, and interactive visualizations to answer scientific and clinical questions.

- Partner with Medical Affairs, HEOR, and cross-functional stakeholders to deliver data-driven insights that support strategic decision-making.

- Apply advanced statistical methodologies for exploratory analyses, comparative studies, predictive modeling, and outcomes research.

- Ensure high standards of reproducibility, documentation, and version control using Git and related tools.

- Support EU JCA evidence needs and contribute to submissions, reports, and scientific communication materials.

Required Skills & Experience:

- 5+ years of hands-on experience working with RWD, HTA analysis, or clinical datasets within Medical Affairs, HEOR, epidemiology, or related domains.

- Expert-level proficiency in R and R-Shiny (mandatory), including deep knowledge of R packages, APIs, functions, and application deployment.

- Strong foundation in advanced statistical methods, data wrangling, and exploratory data analysis.

- Experience working with clinical datasets, including understanding of CDISC standards (SDTM, ADaM), and familiarity with clinical trials across Phases I-IV (especially Phase 3b/4).

- Proven experience building interactive apps and dashboards that communicate complex clinical concepts simply and effectively.

Preferred / Nice-to-Have Skills:

- Knowledge of Python and other open-source analytics or visualization tools (desirable but not mandatory).

- Understanding of regulatory or payer-driven evidence needs such as HTA, EU JCA, or outcomes research.

- Experience with cloud environments, API integration, or full-stack development for Shiny apps.

Soft Skills:

- Strong communication skills with the ability to translate complex clinical data into actionable insights.

- Ability to work collaboratively in a multidisciplinary setting (medical, clinical, data, biostatistics teams).

- High attention to detail and a commitment to scientific rigor.