Healthcare Data Scientist, Predictive Analytics (RWAS) (R1062118) in London, UK bei IQVIA™

Datum der Veröffentlichung 9/25/2019

Stellenauszug

  • Mitarbeiterkategorie:
    Vollzeitbeschäftigung
  • Standort:
    London, UK
  • Jobkategorie:
  • Berufserfahrung:
    Not Specified
  • Datum der Veröffentlichung
    9/25/2019
  • Job ID:
    R1062118

Stellenbeschreibung

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.



Healthcare Data Scientist

Predictive Analytics, Real-World & Analytics (RWAS) Technology

We are looking for a creative, innovative, intellectually curious and entrepreneurial Data Scientist with experience in applying Machine Learning algorithms to solve real-world problems to join our London (Kings Cross) 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

We are looking for a Data Scientist who is keen to apply data engineering and machine learning tools and products at the cutting-edge of life sciences. The primary focus of the role is:

  • Use and understand client requirements to apply ML-focused solutions to highly complex, rich patient-level medical data
  • Communicate technical concepts and analytical outputs to a diverse set of stakeholders (internal and external)
  • Own the delivery of client-facing projects from a technical perspective: Working closely with data engineers, data scientists and consultants in an agile environment to deliver work that adheres to the processes and quality standards set by the team
  • Proactively provide feedback on existing processes and identify areas for improvement across the workflow.

Our ideal candidate will have:

  • An appetite for applying new and existing technologies to challenging problems in health care, i.e. motivated by solving the problem
  • Postgraduate degree or higher in a technical or scientific domain
  • Experience of analytical / machine learning projects in academia or commercial sector
  • Experience in scientific programming languages such as Python and R
  • Knowledge of supervised machine learning methods, such as regularised regression, ensemble tree-based models (e.g. xgboost), support vector machines, deep learning methods, etc.
  • Good grasp of classical statistical methods, such as fitting regression models, inference testing and sampling.
  • Excellent organisation skills with an appetite for working a fast-paced environment
  • Excellent written and spoken communication skills, including ability to present technical concepts to lay audiences, write analysis plans for projects, contribute to proposals / grant applications, pitch ideas effectively and persuasively to clients / internal stakeholders, etc.
  • A proactive, innovative and pragmatic approach to problem solving and an ability to think critically and independently, able to work as part of a cross-functional team.

Bonus points for:

  • Knowledge of healthcare patient-level data
  • Knowledge of epidemiology / biostatistics, particularly analytical issues relating to studies of treatment effectiveness, disease progression, adherence, healthcare utilisation, etc.

  • Work in bioinformatics

  • Knowledge of healthcare / life science issues involving Real-World Evidence

  • Experience with patient-level, longitudinal data.



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 retrospective clinical studies, under-diagnosis of rare diseases, personalised 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 Predictive Analytics team work hand-in-hand with statisticians, epidemiologists and disease area experts 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.



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 maximize 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: R1062118