Artificial Intelligence and Machine Learning careers

AIML

Help shape the future
of IQVIA Healthcare-grade AI™

The healthcare and life sciences industry need more than just AI. They need AI engineered with new levels of speed, precision and trust. We are looking for AI & machine learning experts who want to develop a different class of AI, Healthcare-grade AI™.

Building on our rich history of applying AI for healthcare, we are leveraging the largest, highest-quality healthcare data in the industry, collaborating with multidisciplinary experts, and delivering award-winning AI solutions to accelerate results and improve patient outcomes around the world.

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From developing my technical skills as an individual contributor to furthering my leadership skills as a people manager, IQVIA has supported my career progress every step of the way. I’ve also gained exposure to AI solutions, developed strategic partnerships with both internal and external partners, and have been encouraged to attend conferences, including a recent webinar on how AI and ML are being leveraged to optimize clinical development success.

Greg

Director, Artificial Intelligence Solutions Delivery

IQVIA AI is trained on high-quality data and deep domain expertise. This allows us to connect disparate pieces of healthcare data, from multiple sources, and generate reliable insights that can increase efficiency and accelerate innovation. This enables us to lead the industry in exciting ways – from identifying patients at the earliest stage of disease, to developing new and more effective treatments, to helping people live longer, healthier lives.

Raja

Head of AI and Tech Consulting, EMEA

Advances in science, technology, and healthcare are converging to enable never-before-seen innovations that have the potential to revolutionize patient outcomes. At IQVIA, we are making this potential a reality, and are committed to going beyond the hype to ensure we’re taking a responsible approach, backed by scientific rigor, to get results that change people’s lives for the better.

Christina

Chief Scientific Officer, Real World Solutions

My colleagues and managers have been fundamental to my development whilst working in tech at IQVIA. Their support, feedback and expertise has enabled me to progress within my role. And the team’s enthusiasm has been extremely motivating for me.

Ami

AIML Business Systems Analyst

Greg

Director, Artificial Intelligence Solutions Delivery

Raja

Head of AI and Tech Consulting, EMEA

Christina

Chief Scientific Officer, Real World Solutions

Ami

AIML Business Systems Analyst

Greg

Director, Artificial Intelligence Solutions Delivery

CASE STUDIES

Improving patient outcomes and

closing care gaps

IQVIA is working with life sciences companies, governments, and non-profit organizations to power smarter healthcare with advanced AI capabilities.

Closing care gaps with Social Determinants of Health (SDoH)

Challenge: Social factors such as employment status, financial situation, or stress are useful predictors of health outcomes but are often only captured in unstructured physician notes. For example, NorthShore University HealthSystem found only 0.1% of patient records had these fields completed.

Solution: IQVIA assisted NorthShore with the use of Natural Language Processing (NLP) to assess that unstructured data across multiple sources.

Results: NorthShore is now able to help close care gaps by identifying and screening 56% more at-risk patients. In one example, they were able to identify at least one SDoH risk factor in 30% of their patient population (up from only 0.1%).

Reducing risk of stroke for AFib patients

Challenge: Atrial Fibrillation (AFib) patients are 5x more likely to have a stroke. IQVIA partnered with the UK National Health Service to reduce AFib related strokes through identifying at-risk patients.

Solution: The risk of stroke for AFib patients was predicted using EMR data including age, gender, and clinical risk factors (e.g. Congestive Heart Failure, Hypertension, Stroke/Transient Ischemic Attack, Diabetes, Vascular Disease).

Results: Annual strokes reduced by approximately 22% during the implementation phase compared to the prior period. This also led to an estimated reduction in healthcare costs amounting to an annual savings of approximately $2m.

Improving care for patients with Type 1 Diabetes

Challenge: Nearly 40% of adults with Type 1 Diabetes are initially misdiagnosed with Type 2. IQVIA worked with the Juvenile Diabetes Research Foundation (JDRF) to identify Type 1 patients most likely to be misdiagnosed.

Solution: IQVIA developed an AI algorithm on EMR data, to identify misdiagnosed Type 1 among patients with Type 2 at different points in the patient’s treatment journey.

Results: Inputs into the AI algorithm are routinely collected in EMR data – thus available within any Healthcare Organization (HCO) providing opportunity to deploy the program at scale. The algorithm is currently being prospectively validated at 4 US HCOs testing 2 different scaling paths.

Enhancing routine care for diabetes and CVD

Challenge: The government of one Middle East country is investing in AI to make better healthcare decisions in the diagnosis and treatment of both diabetes and cardiovascular disease.

Solution: IQVIA developed 14 decision support tools that can be used by physicians to help guide screening, improve preventative care and optimise disease management.

Results: The program is being delivered by a cross-functional team of local and global IQVIA experts over a three year period.

Identifying patients at risk for respiratory disease

Challenge: A client launched a new product to treat respiratory disease. They needed help identifying patient cohorts with this specific unmet need to then reach physicians most likely to have these patients.

Solution: IQVIA deployed the AI/ML Platform capability to identify and profile eligible patient populations with unmet needs. The patients were profiled based on sub-national concentration, demographics and other clinical drivers, with focus on physicians treating them.

Results: Patients predicted for high likelihood to have respiratory disease with 86% precision, while removing approximately 30% of non-target patients from the target population data. Furthermore, a 6-month analysis of patients on this new treatment showed a 17% reduction in uncontrolled disease status.

Expertise where it counts

1.2 +

Billion non-identified
patient records

150,000 +

Global data providers connected
to the IQVIA Human
Data Science Cloud

61 +

Petabytes of unique data

13,000 +

Technology experts

Lead the future of healthcare technology

Whether your interests lie in AI engineering, data science, software development, or another technical or analytical area, leverage your expertise to design and build innovative solutions for our healthcare clients. Join our network of 13,000+ technologists across one of our technical specialty areas:

• Frontend
• Backend
• Automation
• Big Data
• Databases
• Event Streams
• Containers
• Cloud Infrastructure
• Information Security
• Testing

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