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

Apply Now

Data Scientist

IQVIA Ltd. (GB80)
City of London
4 days ago
Create job alert

Real-world evidence Data Scientist

Data Standardization and Analytics, Real-World Solutions (RWS)

IQVIA has adopted OMOP/OHDSI as a systematic and standardized approach to real-world evidence (RWE). Data are converted into the OMOP Common Data Model, making queries and analytics interoperable and sharable. In addition, the generation of these queries and tools and its execution can be separated, both physically as well as logically, creating the opportunity to develop code for purposes of descriptive statistics or hypothesis testing in the absence of a direct data access to all data assets being targeted. As a consequence, our team can generate insights across multiple datasets in our collaborators network.

The Data Standardization & Analytics team's mission is to deliver world class and globally scalable projects through:

  • Rapid analytics - to assess study feasibility and availability of data

  • Characterization of patient populations: their demographics, the distribution of their comorbidities, the duration between diagnosis and intervention, treatment patterns etc.

  • Protocol-driven analytics - estimating the association between clinical interventions and their outcomes – benefits and adverse events.

  • Predictive models for determination of populations (phenotypes) or outcomes (patient-level predictions).

  • Network studies – co-ordinating the execution of RWE analytics across multiple external data partner sites.

  • This requires global leadership across technical and data architecture, data manipulation, analytics script and report generation. The solutions are delivered to a variety of clients across life-science, government, payer or provider organizations. The team also curates the largest collection de-identified Real-World Data in the world in OMOP Common Data Model, from different patient care settings in multiple countries worldwide, making it the forefront of “Big Data” in healthcare.

In this role you can expect to:

  • Design & develop analytical packages in R & SQL to extract real-world evidence from OMOP healthcare databases.

  • Translate detailed research specifications into documented instructions, debug routine queries and prepares necessary documentation

  • Contribute to client consultation on study ideation, study design and results interpretation.

  • Support protocol & report writing.

  • Executing retrospective analytical packages as part of OHDSI and other OMOP-based network initiatives.

  • Work collaboratively with OMOP data scientists, plus other team members across DSAE.

  • Support the Senior Data Scientists and other technical experts with building the team’s subject matter expertise with regards to the OMOP common data model.

  • Collaborate with members of the OHDSI community, participate in the OHDSI community through study projects such as study-a-thons, code development and knowledge sharing

  • Support customer focused training sessions and tutorials where necessary

Our ideal candidate will have:

Essential (candidate must have these):

  • R programming (minimum 18 months)

  • Analytical / quantitative research background (preference for big data)

  • Strong communication skills.

Very nice to have (successful candidate will likely have several or all of these skills):

  • Pharmaco-epidemiology or RWE background (or relevant clinical or life science experience). Masters or PhD in a relevant quantitative field.

  • OMOP experience.

  • SQL programming.

  • Consulting experience.

  • AI /ML experience.

  • Shiny dashboard experience

Location and travel:

  • Minimal travel expected to other IQVIA offices (London, East Coast US) or to attend conferences and workshops as required.

  • Home-based

About the Team:

IQVIA Data Standardization and Analytics is a fast-growing and highly successful business, focusing on delivering tangible results to clients across healthcare value chain internationally. We help clients lever patient-level healthcare datasets of varying degree of complexity and richness to understand healthcare treatment patterns and outcomes to make more informed decisions and deliver results. Our approach enables the transformation of the industry utilizing Real-World Evidence (RWE) to provide deeper insight into market dynamics, therapy area changes, outcomes, unmet needs, treatment economics and other scientific and market questions.

Why join IQVIA?

Those who join us become part of a recognised global leader still willing to challenge the status quo to improve patient care. In RWS, you will have access to the most cutting-edge technology, the largest data sets, the best analytics tools and, in our opinion, some of the finest minds in the Healthcare industry.

Driving your Career at IQVIA:

You can drive your career at IQVIA and choose the path that best defines your development and success. With exposure across diverse geographies, capabilities, and vast therapeutic and information and technology areas, you can seek opportunities to change and grow without boundaries.

IQVIA is an Equal Opportunity Employer:

IQVIA is a strong advocate of diversity and inclusion in the workplace. We believe that a work environment that embraces diversity will give us a competitive advantage in the global marketplace and enhance our success. We believe that an inclusive and respectful workplace culture fosters a sense of belonging among our employees, builds a stronger team, and allows individual employees the opportunity to maximize their personal potential.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist - Palantir

Data Scientist - Remote

Data Scientist Python Software - London (IT) / Freelance

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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.