Head of Biological Data Science (Associate Director/Director)
South San Francisco, California
Our client’s technology is based on the science of one of the original CRISPR pioneers who then furthered the technology so that DNA does not need to be cut to accomplish gene regulation. We are looking for a Head of Data Science to tackle complex computational questions with the gene editing space.
Roles and responsibilities:
- Lead the Biological Data Science department consisting of a team of computational biologists, bioinformaticians, and data engineers
- Effectively collaborate with multi-disciplinary teams of translational and pre-clinical scientists on experimental design and analytical approaches to inform preclinical R&D and therapeutic development, as well as clinical development plans, clinical trial designs and clinical trial results
- Oversee high-level strategic planning for developing bioinformatic analysis pipelines to assist pre-clinical therapeutic and platform teams, as well as to enable biomarker readouts for clinical trial development
- Provide expert guidance in the planning, execution, and writeup of computational analyses supporting regulatory filings for novel therapeutic development
- Supervise biostatistical analysis of clinical data in collaboration with the Clinical Operations team and external CROs to support clinical trial development
- Communicate analysis results clearly and effectively cross-team to both experimental scientists as well as non-scientists
Required Qualifications:
- Ph.D. in Bioinformatics, Computational Biology, Genetics/Genomics, Bioengineering, Computer Science, Biostatistics, or a related field
- 5+ years of post-PhD experience in biotech industry, ideally in gene therapy or related next-generation drug development field such as biologics
- Strong analytical/scientific background with experience leading a team of scientists as well as managing external vendors
- Experience analyzing high-throughput sequencing datasets (e.g. CRISPR screens, RNA-seq, ATAC-seq, ChIP-seq, WGBS, scRNA-seq, etc.)
- Experience with clinical biostatistics, clinical trial development and/or regulatory filings in the context of therapeutic drug development
- Strong programming background in Python and R
- Demonstrated ability to communicate research results effectively at a variety of levels (i.e. to leadership, to investors, to scientific experts, etc)
- Experienced in experimental design and working collaboratively cross-team with experimental scientists
Preferred Qualifications:
- Expertise in gene regulation, epigenetics, CRISPR biology, and/or gene therapy
- Theoretical knowledge and practical experience in machine learning / deep learning
- Familiarity with protein engineering (involving model-guided approaches to protein design and molecular dynamic simulations)
- Experience with regulatory submissions and interactions with health authorities (particularly the FDA)
- Familiarity with Github and AWS