Associate Director, Functional Genomics, Data Science

Jobtailor; California (MO); On-site; USD 140,000 - 210,000; Full time

Job summary

Jobtailor is seeking a Lead Bioinformatics Scientist to design and maintain scalable analytics for CRISPR screens. You will integrate multi-omics data and apply ML approaches to accelerate target prioritization, while mentoring PhD-level scientists and guiding the analytics sub team.

The role requires a PhD and 4+ years of experience, strong programming in R/Python, and expertise with AWS/Linux environments, signaling a high-impact contribution to drug discovery programs.

Qualifications

• PhD in a bioinformatics/biostatistics/computational biology field.
• 4+ years of industry or applied academic experience.
• Experience with large scale NGS and functional genomics datasets.
• ML applied to single cell RNA sequencing data.
• Experience designing biological assays and integrating omics results.
• Proficiency in R or Python and Git usage.
• Familiarity with public data repos and AWS/Linux environments.
• Excellent written and oral communication skills.

Responsibilities

• Lead design, development, and maintenance of scalable analytics frameworks for CRISPR screens and QC pipelines.
• Oversee image analysis pipelines for high content and optical CRISPR screens and extract features.
• Integrate genomics, transcriptomics, and proteomics data for target prioritization.
• Apply AI/ML approaches to accelerate target triage and evidence synthesis.
• Mentor PhD-level scientists and set technical direction for analytics sub team.
• Collaborate across disciplines to advance analytical platforms and drug discovery.

Skills

Bioinformatics

Machine Learning

R

Python

NGS Data Analysis

Single Cell RNA Sequencing Analysis

Statistical Hypothesis Testing

Data Integration

Communication Skills

Mentoring

Education

Ph.D. in Bioinformatics/Genomics/Computational Biology

Tools

Git

AWS

Linux

Public Data Repositories

Job description

• Lead the design, development, and maintenance of scalable computational analytics frameworks for pooled, arrayed, single cell, and optical CRISPR screens, including QC pipelines, library design, and longitudinal readout analysis.
• Oversee and actively contribute to image analysis pipelines for high content and optical CRISPR screens, extracting biologically meaningful morphological features to support target prioritization.
• Integrate functional genomics and imaging derived results with high throughput transcriptomics and proteomics datasets to build multi evidence target prioritization packages for multiple stages of drug discovery.
• Leverage cutting edge AI and ML approaches, including LLM powered agentic workflows and network based methods, to accelerate target triage and automate biological evidence synthesis.
• Manage and mentor PhD level scientists, set the technical direction for the analytics sub team, and drive standards for reproducible research and FAIR data infrastructure.
• Collaborate across disciplines with experimental scientists, software engineers, and external partners to advance shared analytical platforms and support Therapeutic Area target identification.

Requirements

• Ph.D. in Bioinformatics, Biostatistics, Computational Biology, Statistics, Computer Science, Mathematics, Genetics/Genomics, or a related STEM field.
• A minimum of 4+ years of industry or applied academic experience.
• A passion for solving biological problems through computational methods with a proactive focus on details and execution.
• Experience with the computational analysis, algorithm development, and biological interpretation of large scale NGS and functional genomics datasets.
• A proven track record of applying machine learning to analyze single cell RNA sequencing data to identify novel patterns and functional insights.
• Previous experience with experimental design of biological assays, statistical hypothesis testing, and integrating results from multiple omics data sources.
• Proficiency in at least one statistical programming language such as R or Python, along with experience using version control environments like Git.
• Familiarity with public data repositories like The Cancer Genome Atlas, Dependency Map, Cancer Cell Line Encyclopedia, and Clinical Proteomic Tumor Analysis Consortium.
• Experience with AWS cloud computing infrastructure and Linux environments.
• Excellent oral and written communication skills.

Core Competencies

Demonstrates expertise in computational analytics frameworks, integrating functional genomics with high throughput datasets, and applying machine learning techniques to biological data analysis. Proven ability to lead teams, mentor scientists, and drive standards for reproducible research.

Highest-signal resume keywords

• Ph.D. In Bioinformatics
• Machine Learning Application
• Statistical Programming (R, Python)
• Experience With NGS Data Analysis
• AWS Cloud Computing Infrastructure

ATS Optimization Keywords

Hard Skills

• Computational Analysis
• Algorithm Development
• Biological Interpretation
• Statistical Hypothesis Testing
• Single Cell RNA Sequencing Analysis
• Experimental Design
• Data Integration
• Quality Control Pipelines
• Longitudinal Readout Analysis
• Morphological Feature Extraction

Soft Skills

• Excellent Communication Skills
• Proactive Focus on Details
• Mentoring

Industry Keywords

• Functional Genomics
• Transcriptomics
• Proteomics
• Drug Discovery
• Therapeutic Area Target Identification

Tools & Technologies

• Version Control (Git)
• Linux Environments
• Public Data Repositories
• FAIR Data Infrastructure
• AI and ML Approaches