Real World Data Programmer (Assoc. Director)

Gilead Sciences
Uxbridge
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Faculty Fellowship Programme - Data Science - May 2026

Data Science Placement Programme

Data Science Placement Programme

Data Science Placement Programme

Job Description

At Gilead, we’re creating a healthier world for all people. For more than 35 years, we’ve tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer – working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world’s biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference.

Every member of Gilead’s team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we’re looking for the next wave of passionate and ambitious people ready to make a direct impact.

We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together.

Job Description

Real-World Evidence (RWE) has become a vital complement to the traditional clinical trial in the demonstration of the value and safety of new medicines. Recognizing its importance, Gilead has established a core RWE Analytics group within the Clinical Data Sciences (CDS) - RWE Organization to support the use of RWE across the discovery, development, and lifecycle of our medicines. Members of this group will be fully embedded alongside their Clinical, Real-World Evidence (RWE), Medical Affairs Research (MAR) and Global Value & Access (GV&A) colleagues, helping to develop and execute their RWE strategies.

As a member of the core RWE Analytics group, individuals will have access to real-world databases in-licensed across Gilead and Kite and act as the stewards of Gilead’s best practices, standards, and methodologies underlying the use of real-world data (RWD).

Job Description

As a member of the CDS-RWE Analytics group, the RWD Analyst reports directly Head of RWE Analytics and is responsible for the design and conduct of statistical analyses of RWD to assess the value of Gilead therapies and perform data visualization and QCs TFLs to communicate results to internal stakeholders in Real World Evidence. The RWD Analyst will align with the Real-World Evidence Therapeutic Area (TA)-aligned Lead to conduct timely, relevant and rigorous analysis of RWD to address critical research questions, as well as collaborate with CDS to develop, refine, and scale data management and analytic procedures, systems, workflows, best practices, and other issues.

Key Responsibilities

Develop and QC TFLs for protocols/reports/manuscripts from RWE research conducted to assess the value of Gilead therapies using RWD (e.g. claims and EHR). QC programming for descriptive and complex studies using RWD. Conduct analyses and develop specifications for descriptive and complex statistics in studies using RWD. Write the statistical analysis plan (SAP) for descriptive and complex studies using RWD, including from internal Gilead-sponsored prospective cohort studies, claims, charge master and EHR in collaboration with RWE TA lead Understand methods and programming to support Comparative Effectiveness Research (CER) analyses, as well as analyses of patient-reported outcomes (PRO) or other patient outcome data Develop and QC TFLs for protocols/reports/manuscripts from RWE research conducted to assess the value of Gilead therapies using RWD (e.g. claims and EHR) Work with RWE researchers to generate code lists for new measures in RWD

Knowledge, Skills and Experience

Master’s degree (e.g. MA, MSc, MPH) inBiostatistics, Epidemiology or related discipline, such as Outcomes Research from an accredited institution, with an extensive background of relevant, post-graduation experience. Doctoral level training with relevant experience is preferred. Direct experience in lieu of academic training is acceptable. Knowledge of real-world data and experience in observational research study design, execution and communication. Strong track record of analysis of a broad range of RWD. Formal training in Programming and demonstrated proficiency in statisticalanalysis programs commonly used in life sciences (e.g. SAS, R).Understanding of epidemiology or outcomes research and the application of retrospective or prospective studies to generate value evidence. Ability to effectively communicate statistical methodology and analysis results. Ability to work effectively in a constantly changing, diverse, and matrix environment. Knowledge of US secondary data sources required; additional experience with international data sources is preferred. Knowledge and experience in qualitative analysis and data sets (e.g., free-text natural language processing, survey data) is preferred.


For jobs in the United States:

As an equal opportunity employer, Gilead Sciences Inc. is committed to a diverse workforce. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, gender, age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job related characteristics or other prohibited grounds specified in applicable federal, state and local laws. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veterans' Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact for assistance.

For more information about equal employment opportunity protections, please view the ‘Know Your Rights’ poster.

NOTICE: EMPLOYEE POLYGRAPH PROTECTION ACT
YOUR RIGHTS UNDER THE FAMILY AND MEDICAL LEAVE ACT
PAY TRANSPARENCY NONDISCRIMINATION PROVISION

Our environment respects individual differences and recognizes each employee as an integral member of our company. Our workforce reflects these values and celebrates the individuals who make up our growing team.

Gilead provides a work environment free of harassment and prohibited conduct. We promote and support individual differences and diversity of thoughts and opinion.

For jobs in France:

Conformément à la Loi « Informatique et Libertés » (06/01/78), nous vous informons du fait que les données personnelles renseignées pourront faire l'objet d'un traitement informatique par Gilead et pourront être transmises aux Organismes Sociaux. Par ailleurs, vous disposez d'un droit d'accès, de rectification et de suppression des données vous concernant. Vous pouvez exercer ce droit en contactant:

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 AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

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

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.