Senior Data Scientist & Machine Learning Manager, RWAS Technology (R1012243) in London, UK at IQVIA™

Date Posted: 5/16/2018

Job Snapshot

  • Employee Type:
    Full-Time
  • Location:
    London, UK
  • Job Type:
    Consulting
  • Experience:
    Not Specified
  • Date Posted:
    5/16/2018
  • Job ID:
    R1012243

Job Description



Senior Data Scientist & Machine Learning Manager

Machine Learning & Artificial Intelligence Solutions, RWAS Technology


We are looking for a creative, innovative, intellectually curious and entrepreneurial Senior Data Scientist / Machine Learning Manager 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


As an experienced, subject matter expert in Machine Learning, we are looking for a Snr Data Scientist who is keen to lead, shape and grow high profile machine learning products at the cutting-edge of life science. The primary focus of the role is to design and oversee the delivery of machine learning products, such as developing algorithms to find undiagnosed patients with rare conditions. Most projects have an important research component, so a strong academic background 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 client pitches, proposal writing and 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/PhD and peer-review publications involving machine learning, and/or;

  • Extensive experience leading the design and delivery of advanced statistical / machine learning projects in the commercial sector end to end with proven delivery capability including capturing requirements, designing analysis plans, interfacing with clients and writing reports / manuscripts.

  • A proactive, innovative and pragmatic approach to problem solving and an ability to think critically and independently.




Our ideal candidate: Tech Skills


  • •Excellent knowledge of supervised machine learning methods, such as regularized regressions, ensemble tree classifiers (e.g. xgboost), Support Vector Machines, Neural Networks, etc.

  • •Strong experience with software development lifecycle

  • •Strong programming skills in Python and/or R. Experience with pySpark, SparkR or Scala.

  • •Solid understanding of best coding practices and version control software such as Git, ability to write clean and efficient code and a good understanding of the data science package landscape.



Bonus points for:

  • Knowledge of healthcare patient-level data
  • Experience with deep learning
  • Knowledge of epidemiology / biostatistics, particularly analytical issues relating to studies of treatment effectiveness, disease progression, adherence, healthcare utilization, etc.
  • 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 & 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 it 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™.


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: R1012243