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Senior Software Engineer, Machine Learning and AI Solutions (R1051511) in London, UK at IQVIA™

Date Posted: 12/12/2018

Job Snapshot

Job Description



Senior Software Engineer

Machine Learning & AI Solutions, RWAS Technology

We are serious about data. We don’t have ping pong or a snooze room. We have a dedicated, collaborative team with meaningful shared goals who can use the most cutting-edge technology, the largest data sets, and the best analytics tools to achieve them. And we have fun on the journey!

We invite you to be part of a recognized global leader still willing to challenge the status quo to improve patient care. You will be in good company, amongst some of the finest minds in Technology and Healthcare.



The Role

Play an essential role as part of a product engineering team, who develop healthcare web applications with machine learning components.

You will lead the development of an analytics platform, both front-end and back-end components, focusing on creating an informative, smooth, and beautiful experience for the users, along with rapid customisation to client needs.

You’ll build upon our microservices architecture and modular UI, ensuring the possibility of deployment in the cloud and on premise. You will work closely with our big data and machine learning teams to achieve the vision.

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.

If you are highly collaborative, innovative, flexible, excellent at communication, writing high quality code and taking initiative, please apply without delay!



Our ideal candidate: Experience

  • You will have a strong background in commercial software development, and 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

  • Significant experience (ideally long-term commercial projects) developing in at least two of the following: Go, TypeScript, JavaScript (ideally ReactJS), Python, Scala, Java, or C++. You might have a lot of experience in just one of these, but ideally you will have at least dabbled in one more.
  • Experience working with REST architectures and API design, or GraphQL.
  • 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 working with cloud technologies such as AWS, GCP, Azure and also container systems like Docker and Kubernetes.


The Team: Machine Learning & AI Solutions

This high-profile team 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 RWAS team, leveraging a vast variety of anonymous patient-level information. The data encompasses IQVIA’s access to over 530 million anonymised patients as well as bespoke, custom partnerships with healthcare providers and payers.

We are looking for a creative, innovative, intellectually-curious Senior Data/Software Engineer to join our RWAS Technology division in London, Kings Cross. This is an exciting opportunity to be part of one of the world's leading Real World Evidence-based teams, working to help our clients answer specific questions globally, make more informed decisions and deliver results.



The Business Unit: Real-World & Analytics Solutions (RWAS) Technology

 “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 Predictive Analytics team within the Real-World & Analytics Solutions (RWAS) Technology division is a fast-growing group of collaborative, enthusiastic, and entrepreneurial individuals. In our quest to harness the value of Real World Evidence (RWE), we are at the centre of IQVIA’s pursuit of machine learning and cutting-edge statistical methods to advance healthcare. Our efforts improve retrospective clinical studies, under-diagnosis of rare diseases, personalized treatment response profiles, disease progression predictions, and clinical decision-support tools. 

We invite you to join IQVIA™.

IQVIA is a strong advocate of diversity and inclusion in the workplace.  We believe that a work environment that embraces diversity will give us a competitive advantage in the global marketplace and enhance our success.  We believe that an inclusive and respectful workplace culture fosters a sense of belonging among our employees, builds a stronger team, and allows individual employees the opportunity to maximize their personal potential.



Job ID: R1051511