Data Analytics Leader

We advance science so that we all have more time with the people we love.

The Data Analytics Leader (DAL) is an expert in data visualization, data analysis and data insights, enabling the stakeholders to efficiently and effectively review and analyze data from internal studies and external published data. The DAL works directly with ECD Clinical disease area leads, Safety Scientists, and other line function colleagues to ensure that indication or disease specific scientific questions are explored thoroughly using creative data analysis and data visualizations through effective collaboration and innovation. The DAL is also responsible for aligning data visualization and data analysis from other line functions.

Your primary responsibility as a Data Analytics Leader (DAL) will be to provide strategic and technical direction to drive the development and implementation of Early Clinical Development (ECD) data review and data visualization at indication, program and study level. You will innovatively develop the tools and processes that are fit-for purpose and create maximum impact to the organization. You will continuously review opportunities to simplify, innovate and collaborate with experts within and outside of ECD to create efficiencies in support of our ECD vision. As a DAL, you will collaborate with cross functions to build the data review/visualization tools to meet the clinical stakeholder's needs at portfolio level.

The DAL manages the implementation of indication data review and the application of tools (e.g., Spotfire® or Rshiny) by providing training, and dedicated support. The DAL contributes to and drives ECD portfolio specific indication or program data review/visualizations that create high impact in ECD.

The Opportunity:

• Strategically uses the internal and external data, develops advanced data visualizations that fits for gRED early clinical development purpose.
• Acts as a main point of contact for Therapeutic Area (TA) leads or disease area leads with questions on specific disease area data exploratory analysis needs.
• Provides guidance and training and consultation for stakeholders on the visualization tools.
• Collaborates within ECD and other line functions to align and simplify processes that prevent redundancy in analytics.
• Uses strong technical expertise and skills to find opportunities for innovation, efficiency and simplification with the mindset of working smarter.

Who You Are:

• Bachelor degree or higher or equivalent education in statistics, computer science, data science, or relevant technical discipline.
• Significant experience in the pharmaceutical/biotech industry.
• Strong/thorough understanding of the end-to-end drug development lifecycle.
• 3 years of experience with clinical data visualization tools is required, such as Spotfire®, tableau, Rshiny and 3 years of experience in creating SDTM, ADaM, and developing TFL is a huge plus.
• Experience with IronPython and JavaScript in Spotfire preferred.
• Prior experience with analytical/statistical data analysis tools/programming languages (e.g. R, SAS, Python, SQL, or other) nice to have.
• Track record of establishing successful internal partnerships with relevant partner organizations.

Relocation benefits are not available for this posting.

Onsite presence, on our South San Francisco campus, is expected for at least 3 days a week.

The expected salary range for this position based on the primary location of South San Francisco, California is $142,400 - $264,400. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.

Benefits

Genentech is an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.