Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Pharmacoepidemiologist – RWE & Data Science

Cubiq Recruitment
London
1 week ago
Create job alert

Job Title: Senior Pharmacoepidemiologist – RWE & Data Science

Location: London (Hybrid)

Salary: £60,000 – £90,000 DOE


About the Role

A venture-backed TechBio company in London is hiring a senior-level epidemiologist or RWE programmer to help build the future of data-driven drug development.


You’ll join a team that’s rethinking the traditional model - developing internal tools, working directly with biopharma partners, and applying real-world evidence to accelerate drug development.


This role combines scientific depth with software fluency. It’s ideal for someone who thrives at the intersection of health data, analytics, and product-led strategy.


Key Responsibilities

  • Design and analyse non-interventional studies, including regulatory-grade and exploratory projects
  • Collaborate with engineering to build internal tools that support and scale RWE applications
  • Engage with external partners to guide RWE strategy and deliver high-quality outputs
  • Translate complex data into actionable insights for internal stakeholders and regulators
  • Lead protocol and SAP development, contribute to CSRs and publication strategy
  • Apply modern causal inference techniques to support study validity and robustness


Ideal Candidate

  • MSc/PhD in Epidemiology, Pharmacoepidemiology or a science-based subject (biochemistry etc)
  • Strong coding skills in SQL plus R or Python (this is non-negotiable)
  • Experience delivering end-to-end observational studies using real-world datasets
  • Proficient in study design, regulatory writing (protocols, SAPs, TFLs, CSRs)
  • Knowledge of coding systems (ICD, SNOMED, GPI, HCPCS) and RWD sources (claims, EHR, registries)
  • Familiar with regulatory trends around pragmatic trials, external control arms, and synthetic cohorts
  • Skilled in handling and cleaning messy, multimodal data
  • Confident using methods such as propensity score matching, IP weighting, and IV analysis
  • Excellent communication skills with the ability to distil complex findings for different audiences


Bonus Experience

  • Prior work in a startup, biotech or agile CRO
  • Hands-on work with MarketScan, Flatiron Health, or Premier datasets
  • Understanding of product development processes in tech-enabled life sciences companies


This is an opportunity to join a company that’s not just running studies, but building the future of drug development infrastructure. If you’ve got the technical depth, strategic mindset and coding fluency to back it up - get in touch.


Apply with a copy of your CV to:

Related Jobs

View all jobs

Senior Pharmacoepidemiologist – RWE & Data Science

Senior Snowflake Data Engineer

Senior Data Scientist

Senior Data Engineer | Cambridge | Greenfield Project

Senior Data Engineer

Senior Machine Learning Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.

Why the UK Could Be the World’s Next Machine Learning Jobs Hub

Machine learning (ML) is becoming essential to industries across the globe—from finance and healthcare to retail, logistics, defence, and the public sector. Its ability to uncover patterns in data, make predictions, drive automation, and increase operational efficiency has made it one of the most in-demand skill sets in the technology world. In the UK, machine learning roles—from engineers to researchers, product managers to analysts—are increasingly central to innovation. Universities are expanding ML programmes, enterprises are scaling ML deployments, and startups are offering applied ML solutions. All signs point toward a surging need for professionals skilled in modelling, algorithms, data pipelines, and AI systems. This article explores why the United Kingdom is exceptionally well positioned to become a global machine learning jobs hub. It examines the current landscape, strengths, career paths, sector-specific demand, challenges, and what must happen for this vision to become reality.