Join us on our exciting journey!
IQVIA™ is The Human Data Science Company™, focused on using data and science to help healthcare clients find better solutions for their patients. Formed through the merger of IMS Health and Quintiles, IQVIA offers a broad range of solutions that harness advances in healthcare information, technology, analytics and human ingenuity to drive healthcare forward.
Machine Learning and AI Solutions, Real World Insights at QuintilesIMS
You will play an essential role as part of a product engineering team, who will develop healthcare web applications with machine learning components. The ability to learn extremely fast and rapidly build skills in cutting-edge technologies is essential. You will need to bring a depth of experience in full stack development and web technologies, be open about your strengths and weaknesses, and quickly identify how to move you and your team to the next step. A broad understanding of the latest data science technologies is a plus but not a requirement.
You will need to understand the full range of tasks involved in constructing effective and beautiful user-facing applications, from the underlying processing to the end-user experience. You will need to be highly collaborative, innovative and flexible. You must be excellent at communication, writing high quality code and taking initiative.
Our ideal candidate: Experience
- You will have a strong background in commercial software development. You will have worked on multiple web applications, both back-end and front-end, with modern languages and frameworks.
- You have experience working with Agile methodology such as Scrum or Kanban and familiarity with software development practices such as Continuous Integration, Behaviour-Driven Development and DevOps. You will have strong opinions on how to design high-quality, maintainable code for the long-term.
- You will have had some commercial experience of data exploration, cleansing, and the processing of messy data and experience working with very large datasets in SQL databases.
- You will have a degree in a quantitative discipline (computer science, mathematics, physics, artificial intelligence or similar).
- Additionally, knowledge of the latest developments in machine learning and some experience of engineering with the relevant technologies on commercial or large academic projects is welcome.
Our ideal candidate: Tech Skills
- Must have experience working with REST architectures and API design.
- Experience (at least one project) working with a variety of data storage and processing technologies such as SQL, Oracle, PostgreSQL, MariaDB, Redis, MongoDB, Hadoop, Spark, Kafka, Cassandra.
- Bonus points for a demonstrable interest (e.g. public GitHub repo, or online course completion) in at least one of the following machine learning libraries (or equivalents): TensorFlow, scikit-learn, Spark MLLib or CRAN packages for machine learning.
- Bonus points for working with cloud technologies such as AWS, GCP, Azure and also container systems like Docker and Kubernetes.
We are strategic thinkers, innovative technologists, deep subject matter experts and data evangelists who are passionate about driving better performance in healthcare through Machine Learning products. We are collaborative, intellectually curious, entrepreneurial and are encouraged to disrupt how our industry works and how we operate on a daily basis. Plus we have the resource and structure of a large company in an environment where we empower our people to create their own solutions and do their own thing. The Machine Learning & Artificial Intelligence team within the Real-World & Analytics Solutions (RWAS) Technology division is the fastest-growing group of collaborative, enthusiastic, and entrepreneurial individuals.
Eradicating disease and improving global healthcare provide a great sense of purpose for the work that we do. We also have a very collaborative working environment, hands-on leadership and use the latest Agile methodologies at the core of our work. Lastly, and perhaps most importantly, we work with very little legacy technology, allowing our technologists the freedom to innovate with their own ideas and solutions. 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 & common 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 & Analytics Solutions (RWAS) Technology
Real-World & Analytics Solutions (RWAS) 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. RWAS 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 RWAS 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 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.
We invite you to join IQVIA™.
We know that meaningful results require not only the right approach but also the right people. Regardless of your role, we invite you to reimagine healthcare with us. You will have the opportunity to play an important part in helping our clients drive healthcare forward and ultimately improve human health outcomes.
Whatever your career goals, we are here to ensure you get there!