Director RWE and Innovative Evidence

Job Description Summary

Location: London (Westworks), United Kingdom
Alternate Locations: Barcelona, Spain and Dublin, Ireland

Working model: All locations have a hybrid working model (12 days per month in the office)

Note: Novartis is not able to offer relocation support for this role. Please only apply if the location is accessible for you.

About this role:

Are you a highly skilled and experienced evidence generation professional? Would you like to help drive innovation and impact in healthcare? Our RWE and Evidence Generation Director will drive the development and implementation of evidence strategies that deliver innovative and scientifically robust evidence to Therapeutic Areas (TAs) for Novartis.

This role will work within the Global Medical Affairs Evidence Generation Oncology & Immunology team in Development, and reports to the Executive Director, Oncology & Immunology.

 

Job Description

Major Accountabilities

• Develop and drive overarching innovative integrated evidence strategies, in collaboration with internal partners, to ensure that the value of our medicines is fully supported by evidence.

• Act as a thought-leader and internal change agent on matters pertaining to the overall creation and implementation of Real World Evidence / Integrated Evidence strategies and tactics.

• Ask the right scientific questions, understand the evidence needs to optimize approval, access and clinical adoption of our medicines, and ideate and make recommendations on fit-for-purpose data and integrated evidence solutions.

• Deliver high quality, rigorous, and fit-for-purpose evidence solutions according to Novartis priorities and opportunities to impact patients and society.   

• Closely collaborate with internal and external partners ensuring scientific rigor in evidence strategy, study design and analyses.

• Lead or contribute significantly to cross-functional, enterprise-wide and external evidence initiatives as well as to new and innovative data and analytic platforms, methodological approaches and technologies, which enable broader and more effective use of integrated evidence to reimagine medicine.

• Work closely with key countries to develop timely, meaningful and robust evidence to support product value demonstration aligned with local needs (patient access, reimbursement, medical education, and patient advocacy).

Minimum Requirements:

• Advanced degree or equivalent education/degree in life science/healthcare required. MBA or equivalent preferred

• 10+ years of industry and/or relevant experience acquired at biopharmaceutical companies, academia, healthcare provider / Payer / HTA, or relevant consultancy companies.

• Deep understanding and experience of RWD/RWE to generate scientifically rigorous and impactful evidence, both from prospective and retrospective studies, including secondary data sources.

• Strong understanding of drug development with proven ability to identify and deliver impactful evidence from retrospective and prospective studies to optimize regulatory approval, market access and clinical adoption.

• Strong cross-functional experience working with Clinical Development, Commercial, Market Access, HEOR, Medical, Safety, and Regulatory colleagues.

• Deep understanding of and experience with research methodology and statistical methods related to retrospective and prospective clinical data analysis, and observational and/or epidemiological research.

• Demonstrated track record leading and executing research projects using RWD from claims, electronic health records, registries, biobanks, or digital applications, including publications. 

Desirable skills:

• Extensive industry experience generating evidence for assets across different stages of drug development.

• Prior leadership experience with international, multidisciplinary drug development, product teams or country organizations

Languages :

• Fluent English (both spoken and written)

• Additional languages are an advantage

 

Skills Desired

Applied Mathematics, Artificial Intelligence (AI), Aws (Amazon Web Services), Big Data, Building Construction, Cloud Computing, Computer Science, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Electrical Transformer, Machine Learning (Ml), Master Data Management, Professional Services, Python (Programming Language), R (Programming Language), Random Forest Algorithm, Statistical Analysis, Time Series Analysis