· LEAD RWD-RCT HYBRID DESIGN STRATEGY: Develop and execute strategies in partnership with molecule teams to incorporate RWD into RCTs using hybrid-design approaches.
· IDENTIFY EVIDENCE NEEDS & RECOMMEND DATA SOLUTIONS: Ask the right scientific questions, understand the evidence needs for research and development, regulatory and market access, and ideate and make recommendations on fit-for-purpose data and analytics 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.
· 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, collaborative groups, initiatives on knowledge-sharing, methodologies, innovations, technology, IT infrastructure, policy-shaping, processes, etc. to enable broader and more effective use of data and analytics to advance science.
· 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)
· Proven ability to translate and communicate complex study design and findings to diverse audiences
· Deep subject matter expertise with proven ability to transfer this expertise across the business; proven track record of setting new standards, advancing the field of expertise (internally and externally) and engaging & influencing executive leaders internally and externally (e.g., in academic setting).
· 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
· 10+ years of experience in pharmaceutical industry
· Proficiency in English, both written and verbal
· Who we are
A member of the Roche Group, Genentech has been at the forefront of the biotechnology industry for more than 40 years, using human genetic information to develop novel medicines for serious and life-threatening diseases. Genentech has multiple therapies on the market for cancer & other serious illnesses. Please take this opportunity to learn about Genentech where we believe that our employees are our most important asset & are dedicated to remaining a great place to work.
Roche is an equal opportunity employer and strictly prohibits unlawful discrimination based upon an individual's race, color, religion, gender, sexual orientation, gender identity/expression, national origin/ancestry, age, mental/physical disability, medical condition, marital status, veteran status, or any other characteristic protected by law.