Senior Data Scientist - London (R1079905) in London, UK at IQVIA™

Date Posted: 7/13/2019

Job Snapshot

Job Description

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.



Senior Data Scientist

Predictive Analytics, RWAS Technology

This is an exciting role for a senior data scientist to join a creative, dynamic and rapidly growing data science team with access to the world’s largest set of healthcare information and the latest technology platforms and analytics software.  You will leverage your machine learning and statistical knowledge and your advanced coding skills to support the team’s modelling methodologies and to contribute to automatized ML solutions in a collaborative and agile environment.



Day-to-day responsibilities include:

  • Designing ML-focused solutions to solve challenging problems in health care by leveraging highly complex, rich patient-level medical data.
  • Building and maintaining software packages and data science tools that enable fast and accurate delivery of client projects.
  • Working closely with data scientists, consultants and data engineers to collaboratively plan and implement new tools to support the business needs.
  • Supporting other data scientists in the use of the systems you build by providing training and on-case technical support.
  • Ideating and developing experiments that supports the evolution of our modelling strategies and the development of future offerings.
  • Carrying out a variety of product development activities, including requirements gathering, package designing, code peer-reviewing and story planning.
  • Mentoring junior team members and proactively contributing to the overall technical and scientific growth of the team.


The Team

Our Predictive Analytics team 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 under-diagnosis of rare diseases, personalised treatment response, 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 several disease areas including Oncology, Neurology, Chronic diseases such as diabetes, and a variety of very rare conditions. The Predictive Analytics team is made of data scientists, statisticians, software developers, experts in real-world data and in the pharma market and it collaborates across the wider global RWI 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.



Our ideal candidate:

Experience

  • Msc in a numerical discipline and 5+years of industry experience or PhD in a technical or scientific domain and 2+yrs industry.
  • Experience in the design and delivery of projects involving advanced statistical methods and machine learning in an academic and/or commercial setting.
  • Familiarity with Agile methodologies, such as Scrum or Kanban, as well as best practices for software development (i.e. version control, unit-testing).
  • Experience in working with large datasets and distributed computing systems.




Key Skills

  • Advanced level programming skills in Python including significant experience using data science and machine-learning packages such as Numpy, Pandas, scikit-learn, SciPy, etc. Additional experience using PySpark a big plus.
  • Ability to translate real-data problems into machine learning problems and to select appropriate machine algorithms for a given problem. Broad knowledge of advanced machine learning techniques (i.e. gradient boosting, ensemble classifiers, regularized regressions, deep learning) particularly in the context of supervised learning and sequential modelling.
  • A set of software-development values that ensures high-quality, readable and maintainable code is produced within an open and collaborative environment.
  • Excellent written and spoken communication skills, including ability to present technical concepts to lay audiences, write clear package documentation, preparing training resources, maintaining efficient communication with the internal stakeholders, etc.
  • A pragmatic approach in scope and design, seeking simple iterative solutions wherever possible to shorten the time-to-value of work. 




Bonus points for:

  • A demonstrable interest (e.g. public GitHub repo, or online course completion) in one of the following machine learning libraries (or equivalents): TensorFlow, Spark MLLib or CRAN packages for machine learning.
  • Knowledge of healthcare / life science issues involving Real-World Evidence and/or experience in working with electronic medical records.
  • Additional experience developing in other object-oriented languages and/or confident user of shell scripting commands.


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 on delivering tangible business results to clients across healthcare value chain internationally, working with key decision-makers and business managers. RWAS teams help clients leverage 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 visualisation, 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 organisations. RWAS also curates the largest collection of de-identified Real-World Data in the world, from different patient care settings in 18 countries worldwide – the RWES Tech team is at the forefront of “Big Data” in healthcare. Through its mission and skills, the RWAS organisation 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 maximise their personal potential.

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! We invite you to join IQVIA™



Job ID: R1079905