Director, Genomics AI/ML for Preclinical Discovery

BioSpace; Boston (MA); On-site; USD 194,000 - 339,000; Full time

Benefits offered by this job

401(k)

Pension

Vacation

Medical benefits

Flexible benefits

Life insurance

Time off & leave

Job summary

Lilly’s RNA Therapeutics group seeks an accomplished computational genomics scientist to lead a PhD-level data science team responsible for pipeline-facing genomics analyses and AI/ML method development. The Director will drive scientific strategy, mentor researchers, and partner with wet lab and project teams to translate insights into portfolio decisions.

Applicants should have a strong track record in genomics data analysis, ML for genomics, and cloud-based workflows, with demonstrated

Qualifications

• PhD in bioinformatics, computational biology, statistics, data science, ML, biophysics or related field, with 4+ years in leadership.
• Proven leadership of scientists in methods development and genomics.
• Strong ML/deep learning background for genomics with dataset design and evaluation skills.

Responsibilities

• Oversee deployment of computational resources for drug discovery genomics efforts.
• Lead, mentor, and grow a PhD-level data science team.
• Define and drive the AI/ML strategy aligned with portfolio needs.
• Advance AI/ML methods for genomics and translate into scalable tools.

Skills

Team leadership

ML for genomics

Genomics data analysis

Cloud computing

Strategic leadership

Communication

Education

PhD in bioinformatics or related field

Tools

Python

R

AWS

GCP

Docker

Job description

Lilly’s RNA Therapeutics group seeks an accomplished computational genomics scientist to lead a PhD-level data science team responsible for pipeline-facing genomics analyses and AI/ML method development. The Director will drive scientific strategy, mentor researchers, and partner with wet lab and project teams to translate insights into portfolio decisions.

Applicants should have a strong track record in genomics data analysis, ML for genomics, and cloud-based workflows, with demonstrated