The Department of Safety Assessment is responsible for the nonclinical safety assessment of all drug candidates in the portfolio of Genentech from the discovery phase up to support of marketed products. Safety Assessment provides scientific leadership and plays an active cross-functional role in the drug development process.
Within Safety Assessment, Development Toxicology provides toxicology support to the Development small molecule and biotherapeutics portfolio from clinical candidate selection up to post-marketing support. We are seeking a Data Scientist to strengthen our computational toxicology capability and support informatics related activities, such as developing computational tools and toxicology databases, within the Department. This role will involve working in a collaborative team environment, as part of the comprehensive safety assessment of Genentech therapeutics as well as working in cross-functional collaborations with computational experts in related disciplines such as computational chemistry, computational DMPK or discovery informatics.
The successful candidate for the role has expertise in the field of toxicology, chemistry, biology, pharmacology or similar, as well as a strong informatics or computer science background, such as bioinformatics, cheminformatics, machine learning or computational biology. The Data Scientist will be an integral part of the computational toxicology team which partners with Discovery Toxicology in developing strategies and incorporating computational tools to support the design of molecules with favorable properties to avoid potential safety liabilities.
This team performs activities such as integrating predictive in silico models for profiling of chemical libraries or compound design, supports problem solving activities within the drug project teams by investigating structure activity relationships and understanding off-target safety issues. The candidate will support and be involved in those activities and is required to have strong skills in data harvesting and curation, as well as data analysis, to understand biological effects. This role will also include working collaboratively with other groups, such as the Investigative Toxicology group and the Non-Clinical Operations group, to leverage data and mechanistic understanding. The candidate will balance the development, integration and promotion of computational approaches with the ad hoc nature of problem solving in project teams as needed, and will be required to have an adaptive and flexible working style.
Working in a collaborative team environment, the Data Scientist provides expert advice/ guidance to peers and senior leaders in Safety Assessment and to project and technical teams and represents Safety Assessment at related internal review boards in support of program advancement. In addition, the successful candidate represents Genentech in the external scientific community and plays an active role in cross-industry initiatives or at scientific conferences/ professional societies. Experience with cross-functional teams and capability to build productive cross-functional internal and external collaborations are desired.
A PhD in toxicology, chemistry, pharmacology or related field as well as demonstrated experience in informatics or computer science along with significant scientific achievements and at least 3 years of experience in the pharmaceutical industry or other relevant organization .or A Masters in toxicology, chemistry, pharmacology or related field with demonstrated experience in informatics or computer science along with significant scientific achievements and 6+ years of relevant experience in the pharmaceutical industry or other relevant organization.
Demonstrated experience in extracting, compiling and analyzing complex data sets for building QSAR/machine learning/AI models is a requirement. It is preferred that the candidate also has additional technical skills in the field of computational chemistry or computational biology.
Expertise in database generation and scripting in R or other widely used programming languages like Python is required.
The successful candidate must also demonstrate strong decision-making, complex problem solving, critical data analysis and interpretation, excellent written and verbal communication skills; and the ability to build productive cross-functional collaborations both within and external to Genentech.