Lead, Functional Genomics Data Science & AI

Jobtailor; California (MO); On-site; USD 180,000 - 240,000; Full time

Job summary

Jobtailor is seeking a senior leader to design and build scalable computational analytics for pooled, arrayed, single-cell, and optical CRISPR screens. You will guide QC pipelines, library design, and longitudinal readouts, while integrating functional genomics with transcriptomics and proteomics data.

You will apply ML/LLM-powered methods, mentor scientists, and drive reproducible research and FAIR data infrastructure across collaborations with scientists and engineers.

Qualifications

• MS in computational biology, biostatistics, biophysics, mathematics, genetics/genomics, computer science or related STEM.
• Minimum 8 years of experience analyzing large-scale NGS and functional genomics datasets.
• Experience with computational analysis, algorithm development, and biological interpretation of large-scale NGS datasets.
• Proven track record applying machine learning to single-cell RNA sequencing data.
• Experience with experimental design, statistical hypothesis testing, and integrating multiple omics data sources.
• Proficiency in R or Python; experience with Git.
• Familiarity with TCGA, DepMap, CCLE, CPTAC.
• Experience with AWS and Linux environments.
• Excellent communication and mentoring skills.
• Up to 10% travel.

Responsibilities

• Lead design and build of scalable analytics frameworks for CRISPR screens.
• Develop QC pipelines and longitudinal readout analysis.
• Mentor scientists and set technical direction for analytics team.
• Drive reproducible research standards and FAIR data practices.
• Collaborate with experimentalists, software engineers, and external partners.

Skills

Machine Learning

R/Python

Single-Cell RNA-Seq

Data Integration

Team Leadership

Education

MS in Computational Biology

PhD preferred

Tools

AWS Cloud Computing

Linux

Git

R Shiny

Job description

Jobtailor is seeking a senior leader to design and build scalable computational analytics for pooled, arrayed, single-cell, and optical CRISPR screens. You will guide QC pipelines, library design, and longitudinal readouts, while integrating functional genomics with transcriptomics and proteomics data.

You will apply ML/LLM-powered methods, mentor scientists, and drive reproducible research and FAIR data infrastructure across collaborations with scientists and engineers.