Senior Epidemiologist

Description:

Cubiq Recruitment is partnering with a VC-backed biotech startup in London that is on a mission to revolutionize the traditional drug development model. They are seeking a Senior Epidemiologist / RWE Programmer to join their innovative and fast-growing team. This hybrid, full-time position blends scientific expertise with coding proficiency, ideal for candidates eager to contribute at the intersection of real-world evidence (RWE), clinical data, and product development.

As a Senior Epidemiologist, you will lead and execute regulatory-grade and exploratory non-interventional studies, collaborate with software engineering teams to build internal data tools, and work directly with external biopharma partners to drive impactful, data-led decision-making. You will play a critical role in applying modern causal inference techniques, guiding RWE strategy, developing protocols and SAPs, contributing to clinical study reports (CSRs), and engaging with regulators and stakeholders.

Key Responsibilities:

• Design and analyze observational, non-interventional studies

• Lead regulatory-grade RWE projects and deliver strategic insights

• Collaborate with engineering on internal tool development

• Translate complex clinical data into regulatory and commercial value

• Engage in publication strategy, develop study protocols, SAPs, and CSRs

• Apply statistical methods such as propensity score matching, IP weighting, and instrumental variable analysis

Candidate Requirements:

• MSc/PhD in a relevant scientific field

• Strong proficiency in SQL and R or Python

• Familiarity with coding systems like ICD, SNOMED, GPI, HCPCS

• Comfortable with messy and multimodal datasets

• Knowledge of regulatory approaches to pragmatic trials, synthetic cohorts, and external control arms

• Excellent verbal and written communication

Desirable (Bonus) Experience:

• Previous work in a startup, biotech, or agile CRO

• Experience building reproducible workflows or data tools with engineers

• Familiarity with product development processes in tech-enabled life sciences