Senior Data Analyst

Warman O'Brien
Leeds
8 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

HR Senior Data Analyst

Senior Power BI Data Analyst

Senior Data Engineer

Senior Data Analyst – RWE | Global CRO – Client FSP | UK & Europe | Home based |


We’re hiring a Senior Data Analyst to join our clients expanding Real-World Evidence team where you will be fully embedded within our client’s FSP model at a global pharma. This is a fully integrated role supporting oncology observational research, with a strong focus on Flatiron Health data.


You’ll play a key role in advancing real-world insights in oncology, leading programming, analyses, and collaborating cross-functionally with epidemiologists, data scientists, and external partners.


If you're experienced with Flatiron data and thrive in complex, matrixed environments, this is your opportunity to drive meaningful change in cancer research.


What you’ll be doing:

  • Lead statistical programming and analytics using Flatiron Health and other real-world data (RWD) sources, including claims, EHR, genomic, and HEOR data.
  • Develop statistical analysis plans, specifications, and contribute to study reports.
  • Evaluate data feasibility, build patient cohorts, and define/validate variables aligned to oncology study goals.
  • Integrate data across sources and ensure quality control through automation and checks.
  • Deliver analyses on time, on budget, and in line with quality expectations for multiple studies.
  • Collaborate with epidemiologists and scientific teams to refine coding logic, variable definitions, and workflows.
  • Act as a technical and analytical resource for complex RWD projects.


What you will need:

  • Master’s degree (with 5–8 years' experience) or PhD (with 2+ years) in Biostatistics, Epidemiology, Data Science, or a related field.
  • Extensive experience using Flatiron Health data for real-world oncology research.
  • Expertise in programming oncology-specific methodologies, such as deriving lines of therapy and performing survival analyses.
  • Proficiency in SAS (preferred) or R.
  • Proven experience in real-world studies, especially handling large, complex datasets.
  • Strong organization, prioritization, and communication skills with a sharp eye for detail.


What’s in it for you:

  • An exciting opportunity to support innovative clinical research for a leading biotech sponsor, while being part of a globally recognized organization known for its scientific excellence and commitment to improving patient outcomes.
  • Generous remuneration and benefits package.
  • Fully remote role across the UK & Europe.


What to do next:

If this opportunity is of interest, please apply now with your CV as the organisation are looking to welcome the Senior Data Analystonboard as soon as possible.

Not what you’re looking for?

Please contact Jo Fornaciari on +44 7488 822 859 for a confidential discussion about potential opportunities.

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.