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Senior Statistician / Data Scientist, Predictive Analytics (R1010179) in London, UK at IQVIA™

Date Posted: 1/25/2018

Job Snapshot

  • Employee Type:
  • Location:
    London, UK
  • Job Type:
  • Experience:
    Not Specified
  • Date Posted:
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Job Description

Predictive Analytics, RWI Technology

Our Predictive Analytics team within the Real World Insights (RWI) 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. 

We are looking for a creative, innovative, intellectually curious and entrepreneurial Senior Statistician / Data Scientist to join our London-based team.

This is an exciting opportunity to work in one of the world's leading RWI teams working with Real World Insights to help our clients answer specific questions globally, make more informed decisions and deliver results.

The team

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 Predictive 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 role

This is an exciting role for a Senior Statistician / Data Scientist who is keen to lead, shape and grow a high profile and highly motivated data science team at the cutting-edge of life science, blending solutions involving biostatistics and machine learning. The role involves delivering complex projects, ensuring statistical designs are truly innovative and fit-for-purpose, and supporting software engineers / data scientists in automating processes and enabling solutions to be scalable and best-in-class. Whilst in-depth knowledge of machine learning is not required (though some knowledge is a distinct preference), the candidate must be enthusiastic to up-skill in machine learning and to actively engage in the dialogue between classical statistical theory and empirically-driven machine learning methods.

Our ideal candidate: Experience

  • Outstanding advanced statistical expertise, as demonstrated through multiple peer-review publications, strong academics (PhD in medical statistics / biostatistics preferred) and leadership roles (e.g. scientific steering committees, team lead, thought leadership whitepapers, etc.)
  • Extensive experience leading the design and end-to-end delivery of advanced statistical / machine learning projects with proven delivery capability including writing requirements, protocols, statistical analysis plans, reports, abstracts, manuscripts, etc.
  • Demonstrable and successful project management and team management experience, including leading teams and overseeing multiple projects simultaneously
  • Flexible and adaptable in a client focused, results driven environment
  • Comfortable and capable of liaising directly with senior stakeholders (internally and externally)
  • A proactive, innovative and pragmatic approach to problem solving and an ability to think critically and independently.

Our ideal candidate: Tech Skills

  • Excellent grasp of classical statistical methods, such as fitting regression models, survival analysis, inference testing and sampling as well as in-depth knowledge of study design pertaining to healthcare (particularly relating to studies of treatment effectiveness, disease progression, adherence, healthcare utilization, etc.)
  • Excellent knowledge of supervised machine learning methods, such as regularized regressions, ensemble tree classifiers (e.g. xgboost), Support Vector Machines, Neural Networks, etc. (desirable).

You can drive your career at IQVIA and choose the path that best defines your development and success. With exposure across diverse geographies, capabilities, vast therapeutic and information and technology areas, you can seek opportunities to change and grow without boundaries.

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: R1010179