UI/UX Lead, Machine Learning & AI Solutions - RWAS Technology (R1012245) in London, UK at IQVIA™

Date Posted: 7/5/2018

Job Snapshot

Job Description



UI/UX Lead

Machine Learning & Artificial Intelligence Solutions, RWAS Technology


The role

As an experienced, creative UI/UX developer, we are looking for someone who is keen to lead, shape and develop the UI for our Machine Learning products at the cutting-edge of life science. The primary focus of the role is to design and develop the UI of our core Machine Learning platform, in line with client requirements, and also recommend creative new designs to help the client interact better with our rich data and powerful Machine Learning algorithms that detect undiagnosed patients.




A typical day could include;

  • Designing and developing an appealing and engaging front end for the Machine Learning core platform
  • Driving UI design and development forward, bringing innovative ideas to the table
  • Working closely with software developers, data architects, Product Owners, development & Operations teams to understand/define requirements, deliverables, and provide the necessary engineering expertise & support to ensure UI delivery
  • System development, big data analysis visualisation and troubleshooting
  • Configuration and prototyping of new systems
  • Contributing to the definition and adoption of technical standards
  • Performing peer code reviews
  • Participating in design, development and implementation of the system front-end
  • Acting as a fully seasoned/proficient technical resource, providing technical knowledge and capabilities as team member and individual contributor
  • Working with the team or as an individual contributor to perform analysis, design, development and testing of solutions to meet requirements
  • Working under minimal supervision and self-managing work load to ensure delivery of solutions.


Our ideal candidate: Experience & Education

  • Bachelor’s Degree in Information Technology, Software Engineering, Computer Science, Mathematics or other UI creative related field
  • Experience in designing and developing UI in software development or other commercial organisations
  • Experience with product lifecycle and agile development.



Our ideal candidate: Tech Skills

  • Deep experience on CSS
  • React
  • Redux
  • TypeScript or JavaScript ES6
  • Front-end testing frameworks – Jest, Enzyme or similar like Mocha
  • Version control
  • Understands cross-browser / platform issues and solutions
  • Responsive web design
  • Experience working with REST APIs and JSON.



Bonus points for:

  • Progressive Web Apps
  • SQL database such as MySQL or PostgreSQL
  • Good eye for aesthetics
  • Some experience with UX / UCD
  • Knowledge of latest web standards, including accessibility
  • Scrum / Agile
  • Vue
  • Plotly or d3
  • NodeJS
  • GraphQL.



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.


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. This Centre of Excellence also curates the largest collection de-identified Real-World Data in the world, from different patient care settings in 18 countries worldwide – the RWAS Technology CoE is at the forefront of “Big Data” in healthcare.  Through its mission and skills, the RWAS group is transforming the way clients create new insights and deliver improved healthcare research and patient outcomes.




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: R1012245