As a Principal 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 a good understanding of molecule and disease area strategies, healthcare environments, as well as strong scientific and technical data science expertise. You will need strong strategic, collaboration and communication skills, as well as an entrepreneurial mindset, to transform the way we use data and analytics to develop and deliver medicines for our patients.
As Principal Data Scientist you will typically be expected to contribute to the molecule/disease area for multiple or complex projects with minimal supervision. You will contribute to the design and analysis of real world data retrieved through a novel patient-centered approach. You are expected to closely collaborate with our external research partners and internal stakeholders to ensure study implementation. We will look to you as a positive role model for peers and you will coach colleagues to improve in their role with both technical and interpersonal skills.
MSc, PhD or similar qualification in a quantitative data science discipline (e.g., statistics/ biostatistics, epidemiology, outcomes research, public health, medicine, psychology)
Demonstrated track record of developing and executing epidemiological or outcome research projects, 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
Track record of effectively working in a matrix environment with global, international team members coming from scientific, business and operational backgrounds, using influence without authority
PhD degree as listed in Minimum Qualifications
4+ years of relevant work experience
Proven ability to translate and communicate complex study design and findings to diverse audiences
Experience with external collaborations