IQVIA™ is the leading human data science company focused on helping healthcare clients find unparalleled insights and better solutions for patients. Formed through the merger of IMS Health and Quintiles, IQVIA offers a broad range of solutions that harness the power of healthcare data, domain expertise, transformative technology, and advanced analytics to drive healthcare forward.

Data Scientist - Deep Learning

Machine Learning & Artificial Intelligence Solutions,

We are looking for a creative, innovative, intellectually curious and entrepreneurial Data Scientist with experience in developing Machine Learning software to join our London-based team.

This is an exciting opportunity to work in one of the world's leading human data science teams working with Real World Insights to help our clients answer specific questions globally, make more informed decisions and deliver results.

The role

We are looking for a Data Scientist who is keen to build machine learning products at the cutting-edge of life sciences. The primary focus of the role is to develop ML algorithms on high scale-high complexity rich medical data to predict answers to healthcare challenges. There is an important research component, so a strong academic background and some software development experience is preferable (the role includes opportunity to publish and participate in academic conferences).

In addition, there is scope for development in other key areas:

• Product Development- Working closely with software engineers, system architects and data scientists to build automated and scalable routines / libraries.
• Business Development- Supporting business development initiatives, including technical support for product sales, thought leadership (includes publications, presentations at academic conferences, client workshops, etc.).

At IQVIA we appreciate and nurture individual talent. Therefore, the exact blend of responsibilities and individual career development will in part depend on the skill set and aspirations of the successful candidate.

Our ideal candidate: Experience

• ·MSc or PhD in Machine Learning, Computer Science, Physics, Bioinformatics or similar

• ·Analytical experience within a top academic or commercial organisation where data-led problem solving was core part of the role.

• ·Experience with the design and delivery of advanced machine learning projects in either academic or commercial settings.

• ·A proactive, innovative and pragmatic approach to problem solving and an ability to think critically and independently, able to work as part of a cross-functional team.

Our ideal candidate: Tech Skills

• Good knowledge of deep learning methods (e.g. Convolutional neural networks, Recurrent neural networks, Transformer)
• Hands-on experience with Neural Network libraries (e.g. TensorFlow, Keras, PyTorch).
• Good knowledge of supervised machine learning methods, particularly gradient boosting classifiers (e.g. XGBoost, LightGBM)
• Good programming skills in Python.
• Understanding of what it takes to write clean code and some experience of the data science package landscape, for example numpy, pandas, matplotlib, etc.
• Experience with software development lifecycle.

Bonus points for:

• Experience with explainability methods (e.g. SHAP)
• Experience with Graph Neural Networks
• Knowledge of healthcare patient-level data
• Knowledge of epidemiology / biostatistics, particularly analytical issues relating to studies of treatment effectiveness, disease progression, adherence, healthcare utilization, etc.
• Work in bioinformatics.
• Knowledge of healthcare / life science issues involving Real-World Evidence.
• Experience with patient-level, longitudinal data.

The Team

Our Machine Learning & Artificial Intelligence team within the Real-World & Analytics Solutions (RWAS) Technology division is a fast-growing group of collaborative, enthusiastic, and entrepreneurial individuals. In our never-ending quest for opportunities to harness the value of Real World Evidence (RWE), we are at the centre of IQVIA’s advances in areas such as machine learning and cutting-edge statistical approaches. Our efforts improve retrospective clinical studies, under-diagnosis of rare diseases, personalized treatment response profiles, disease progression predictions, and clinical decision-support tools.

You will join this high-profile team to work on ground-breaking problems in health outcomes across disease areas including Oncology, Neurology, Chronic diseases such as diabetes, and a variety of very rare conditions. The Machine Learning & Artificial Intelligence Analytics team work hand-in-hand with statisticians, epidemiologists and disease area experts across the wider global RWE Solutions team, leveraging a vast variety of anonymous patient-level information from sources such as electronic health records. The data encompasses IQVIA’s access to over 530 million anonymised patients as well as bespoke, custom partnerships with healthcare providers and payers.

The Business Unit: Real-World Solutions (RWS) Technology

Real-World Solutions (RWS) is a market-leading, fast-growing and highly successful business, focusing upon delivering tangible business results to clients across healthcare value chain internationally, working with key decision-makers and business managers. RWS teams help clients lever complex clinically rich patient-level healthcare datasets to understand healthcare treatment patterns and outcomes to make more informed decisions, and deliver results.

The RWS Technology mission is to deliver world class and globally scalable technology platforms and analytics applied to complex and large scale clinical datasets, to support IQVIA’s ongoing and rapid growth in Real World Evidence, as well as the development of new product lines - this requires global leadership across technical and data architecture, software development and data visualization, privacy management, analytical methods, data science, machine learning, deep learning and natural language processing (NLP) - building upon 100s of novel technologies and methods either published in peer reviewed journals or patented by our team.

The solutions are delivered to a variety of clients across life-science, government, payor or provider organizations. The CoE also curates the largest collection of de-identified Real-World Data in the world, from different patient care settings in 18 countries worldwide – the RWES Tech CoE is at the forefront of “Big Data” in healthcare. Through its mission and skills, the RWES is transforming the way clients create new insights and deliver improved healthcare research and patient outcomes.

Join Us

Making a positive impact on human health takes insight, curiosity, and intellectual courage. It takes brave minds, pushing the boundaries to transform healthcare. Regardless of your role, you will have the opportunity to play an important part in helping our clients drive healthcare forward and ultimately improve outcomes for patients.

Forge a career with greater purpose, make an impact, and never stop learning.