Data Scientist, PHC Analytics

Roche

Welwyn, AL7 1TW

Ref: 3597975147

As a Data Scientist within our Personalized Healthcare function you will work with meaningful data to generate impactful evidence and insights on our molecules/ medicines and patients, that support R&D, advance scientific and medical knowledge, and enable personalized patient care and access.

You will collaborate with peers within the function and across the organization to develop evidence generation strategies, identify evidence gaps and data sources, design and execute studies, and implement analyses to address molecule and disease area questions. The data will be varied in type -- patient-level clinical data, supplemented with deep patient data such as omics (e.g. genomics, proteomic), imaging, digital health, etc. Source data will be diverse -- real-world data, including patient registries, electronic medical records, claims, biobanks, and clinical trials. The evidence and insights will be used to inform the research and development of our molecules, and support healthcare decisions by patients, physicians, health authorities, payers, and policy-makers. You will also contribute to functional, cross functional, enterprise-wide or external initiatives that shape our business and healthcare environments. This will require strong statistical, data science and analytical expertise as well as a good understanding of molecule and disease area strategies and healthcare environments,. You will need strong strategic, collaboration and communication skills, as well as an entrepreneurial mind-set, to transform the way we use data and analytics to develop and deliver medicines for our patients.

As Data Scientist you will typically be responsible for a molecule/indication and partner with cross-functional teams and external partners with considerable independence.

RESPONSIBILITIES

IDENTIFY EVIDENCE NEEDS & RECOMMEND DATA SOLUTIONS:

DEVELOP DATA STRATEGY & GAIN ACCESS TO DATA: Develop strategic plans to access fit-for-purpose data sources to support evidence generation, and gain access to data through collaboration or data generation.

DIVE INTO DATA: Develop a comprehensive and deep understanding of the data we work with and foster learning with colleagues using analytical tools and applications to broaden data accessibility and advance our proficiency/efficiency in understanding and using the data appropriately.

BE AN EXPERT IN APPLYING METHODS: Stay current with and adopt emergent analytical methodologies, tools and applications to ensure fit-for-purpose and impactful approaches. Understand the underlying principles of the data science and statistical methodologies and ensure that they are applied appropriately

PRODUCE HIGH QUALITY ANALYSES: Apply rigor in study design and analytical methods; plan for data processing; design a fit-for-purpose analysis plan, assess effective ways of presenting and delivering the results to maximize impact and interpretability; implement and/or oversee the study, including its reporting; ensure compliance with applicable pharma industry regulations and standards.

INTERPRET AND SHARE RESULTS: Communicate findings to internal stakeholders, regulatory, health technology assessment (HTA) bodies and scientific communities; publish results; participate in external meetings and forums to present your insights (e.g. congress/conference).

COLLABORATE & SHAPE: Collaborate and contribute to functional, cross-functional, enterprise-wide or external data science communities, networks, collaboratives, initiatives or goals on knowledge-sharing, methodologies, innovations, technology, IT infrastructure, policy-shaping, processes, etc. to enable broader and more effective use of data and analytics to support business.

MINIMUM QUALIFICATIONS

  • MSc, PhD or similar qualification in a quantitative data science discipline (e.g., statistics/ biostatistics, epidemiology, bioinformatics, health economics, computational biology, computer science, mathematics, outcomes research, public health, biology, medicine, psychology)
  • Demonstrated track record of developing and execution of data science research projects, patient-level data analyses (e.g., real world data, surveys, clinical trials, registries, claims, genomic or imaging data) with publications and presentations
  • Demonstrated experience with managing project scope and driving delivery in an evolving environment requiring proactivity and effective problem-solving and prioritization when faced with challenges
  • Demonstrated strong collaboration skills and excellent communication skills
  • Demonstrated entrepreneurial mindset and self-direction, ability to teach others and willingness to learn new techniques
  • Proficiency in English, both written and verbal


PREFERRED/ADDITIONAL QUALIFICATIONS

Analytics

  • PhD degree in a quantitative discipline as listed in Minimum Qualifications
  • Fluency in statistical programming languages (R, Python, etc.)
  • Understanding of the underlying theory and experience in application of a range of data modelling techniques (multivariate modelling, time-to-event analysis etc.)
  • Experience implementing advanced analytics approaches (machine learning, longitudinal data analysis, etc.)
  • Experience with technologies required to undertake analyses on large data sources or with computationally intensive steps (SQL, parallelization, Hadoop, Spark, etc.)
  • Experience producing interactive outputs (Shiny, etc.)
  • Contributor to open source packages, libraries or functions
  • Experience implementing reproducible research practices like version control (e.g., using Git) and literate programming
  • Experience using observational study design to analyse RWD (non-interventional studies, electronic medical records, claims, disease registries etc.)

If you are proud of contributing and feel you have the commitment to teamwork and innovation that we are seeking, then Roche is the organisation for you. In return we offer a competitive salary plus the excellent benefits you would expect from a blue-chip organisation, including a genuine interest in your development and progression.


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