Senior Data Scientist, CompBio

The Opportunity

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. 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 as part of a cross-functional team of life scientists, data scientists, bioengineers, software engineers, and machine learning scientists.

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 in South San Francisco.

Responsibilities

Multimodal Analysis & Target Discovery

• 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.

Experimental Partnership

• 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.

Analytical Rigor & Communication

• 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.

Qualifications

Experience & Qualifications

• Education & Tenure: Ph.D. in computational biology, systems biology, bioengineering, computer science, machine learning, or a related discipline, with 3+ years of working experience post-graduation.
• Data Modality Depth: 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.
• Statistical Foundation: Deep understanding of statistical modeling and data analysis, with a demonstrated ability to rigorously interpret complex datasets and generate mechanistic hypotheses.
• Biological Grounding: An understanding of molecular biology or disease biology (e.g., neurological, cardiovascular, or metabolic disorders).
• Programming Skills: Strong programming ability and proficiency with Python scientific packages such as NumPy and pandas.
• Publication Record: Meaningful contributions to high-quality work published in relevant computational biology, systems biology, life sciences, or biomedical venues.

Core Competencies

• Collaborative Communicator: You communicate effectively and collaborate well with people of diverse backgrounds and job functions.
• Engineering Discipline: You write well-commented code and documentation and are familiar with coding best practices such as version control and code review.