Senior Data Scientist, CompBio at Insitro · LumiJobs
senior
$183k–$194k
H1B: yes
Responsibilities
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.
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
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
