Senior Data Scientist, CompBio
About The Position
State-of-the-art technologies that measure multiple cellular aspects of in vitro biology are at the heart of insitro's efforts to accelerate drug development. Computational biology is key to elucidating the relationship between these phenotypes and human disease and translating them into actionable outcomes. We are looking for a computational biologist with expertise across diverse data modalities, including deep experience in either omics or imaging readouts, a strong understanding of cell and disease biology, and fluency with state-of-the-art analysis techniques. Your expertise will help the team navigate the complexities of identifying therapeutic targets from diverse data, elucidating biological mechanisms, and championing a culture of statistical rigor and experimental design to ensure our analyses meet the highest scientific standards. In this role, you will directly impact target prioritization and drug development efforts, advance our understanding of diseases, and aid the development of new treatments. You will be part of a cross-functional team of life scientists, data scientists, bioengineers, software engineers, and machine learning scientists who strive to identify therapeutic targets and develop drugs of high efficacy and low toxicity. Based in South San Francisco, this position reports directly to the Head of Computational Biology and ML-Omics and offers an in-person hybrid schedule of three days per week. You will be joining a vibrant biotech startup with many opportunities for significant impact. You will work closely with a highly talented team, learn a broad range of skills, and help shape insitro's culture, strategic direction, and outcomes. Join us, and help make a difference to patients!
Requirements
- Ph.D. in computational biology, systems biology, bioengineering, computer science, machine learning, or a related discipline, with 3+ years of working experience post-graduation
- Hands-on experience with diverse data modalities, including at least one of the following: single-cell RNA-seq, fluorescence microscopy, spatial proteomics or transcriptomics, or label-free microscopy
- Deep understanding of statistical modeling and data analysis, with a demonstrated ability to rigorously interpret complex datasets and generate mechanistic hypotheses
- An understanding of molecular biology or disease biology (e.g., neurological, cardiovascular, or metabolic disorders)
- Strong programming ability and proficiency with Python scientific packages such as NumPy and pandas
- Meaningful contributions to high-quality work published in relevant computational biology, systems biology, life sciences, or biomedical venues
- You communicate effectively and collaborate well with people of diverse backgrounds and job functions
- You write well-commented code and documentation and are familiar with coding best practices such as version control and code review
Responsibilities
- Synthesize Multimodal Insights: Draw insights from multimodal analyses (microscopy, spatial proteomics, bulk/single-cell RNA-seq, human cohort data) to uncover disease mechanisms and generate therapeutic hypotheses
- Identify Therapeutic Targets: Analyze diverse data from disease-relevant in vitro models to identify potential therapeutic targets from perturbation screens
- Discover Biomarkers: Analyze data from diverse sources to identify and validate potential biomarkers for monitoring disease status and progression
- Partner on Experimental Design: Work with experimental biologists to design, troubleshoot, and optimize experiments that generate and validate mechanistic and therapeutic hypotheses
- Provide Domain Expertise: Bring statistical and computational expertise to guide assay development and the biological interpretation of results
- Benchmark and Calibrate: Calibrate analysis tools and workflows, define performance metrics, and conduct benchmarking to select fit-for-purpose solutions
- Communicate Findings: Share results with cross-functional stakeholders through reports, visualizations, presentations, and publications
Benefits
- Annual Performance Bonus Plan
- Equity Incentive Plan
- 401(k) plan with employer matching for contributions
- Excellent medical, dental, and vision coverage as well as mental health and well-being support
- Open, flexible vacation policy
- Paid parental leave of at least 16 weeks to support parents who give birth, and 10 weeks for a new parent (inclusive of birth, adoption, fostering, etc)
- Quarterly budget for books and online courses for self-development
- New hire stipend for home office setup
- Monthly cell phone & internet stipend
- Access to free onsite baristas and daily lunch for employees who are either onsite or hybrid
- Access to a free commuter bus network that provides transport to and from our South San Francisco HQ from locations all around the Bay Area
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
