Machine Learning Engineer, Healthcare & MedTech

Key Skills

Big Data Technology, Deep Learning, PySpark, Python Programming, XGBoost

Job Description

We are looking for an innovative, collaborative, intellectually curious and entrepreneurial Machine Learning Engineer to join our AI for Healthcare & MedTech data science team based in King of Prussia (PA, USA). This is an exciting opportunity to join a fast-moving start-up style group within one of the world's leading human data science companies. The primary focus of the role is to develop ML solutions on highly complex, large-scale medical data to deliver patient-level alerts to healthcare providers across the world.

A TYPICAL DAY MIGHT INCLUDE:

• Working with the team and client to shape and develop requirements for answering ambitious life science questions (e.g. can we predict a rare disease diagnosis or an optimal dosing frequency in patients?) along with solutions for applying predictive analytics methods within infrastructures specific to each healthcare provider project.
• Addressing those requirements by developing and applying appropriate ETL processes (for cohort and feature creation from the raw data) and machine learning methodology (for constructing predictive models in an unbiased manner).
• Researching machine learning techniques that could be used to improve our offering.
• Communicating technical concepts and analytical outputs to a diverse set of stakeholders (internal and external).
• Proactively identifying opportunities for innovation and areas for improvement across the workflow.

IDEALLY YOU WILL HAVE:

• Postgraduate degree or higher in a technical or scientific domain plus at least one year of experience working in a technical / consulting environment involving machine learning, preferably in a commercial setting.
• Strong scientific programming skills (ideally in Python) and a track record of working on a range of computational challenges (both within and outside machine learning development).
• Appetite for applying new and existing technologies to challenging problems in healthcare, i.e. motivated by solving the problem.
• Knowledge and practical experience of applying supervised machine learning methods, such as regularized regression, ensemble tree-based models (e.g. xgboost) and deep learning methods.
• Excellent organization skills and ability to deliver results to deadlines.
• Excellent communication skills, including ability to present technical concepts clearly (in writing, face-to-face discussions and on conference calls), write project analyses, pitch ideas effectively and persuasively to clients / internal stakeholders, etc.
• A proactive, innovative and pragmatic approach to problem solving, and an ability to think critically and independently.
• Ability to work collaboratively as part of a cross-functional and global team (with members in India and the US as well as in London).

BONUS POINTS FOR:

• Experience in an informatics/data science team of a healthcare organization, including knowledge of healthcare data, EMR integration, types of environments used for data solution development/deployment, etc.
• PySpark / big data experience.
• Knowledge of epidemiology / biostatistics, particularly analytical issues relating to studies of treatment effectiveness, disease progression, adherence, healthcare utilization, etc.

THE TEAM:

“Big Data” is changing the way that the healthcare world operates and, now more than ever, the key to better patient outcomes is through better use of technology, seamlessly integrated information and analytics. Our AI for Healthcare and MedTech team within the Real-World Analytics and AI (RWAAI) division is a fast-growing group of collaborative, enthusiastic, and entrepreneurial individuals. We are at the center of IQVIA’s pursuit of machine learning and cutting-edge statistical methods to advance healthcare. Our efforts improve under-diagnosis of rare diseases, personalized treatment response profiles, disease progression predictions, and clinical decision-support tools and have a direct impact on patient care.

You will join this high-profile team to work on ground-breaking problems in health outcomes across disease areas including Ophthalmology, Oncology, Neurology, Chronic diseases (such as diabetes), and a variety of very rare conditions. The team works 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. The data encompasses IQVIA’s access to over 530 million anonymized patients as well as bespoke, custom partnerships with healthcare providers and payers.