Director of Bioinformatics and Machine Learning

Description

The company uses information from a simple blood draw to detect disease early and guide treatment, with a focus on cell-free DNA (cfDNA) testing.

This director role leads bioinformatics and machine learning work on technology and biomarker research for the cancer early detection programs, covering multi-cancer early detection (MCED), tissue-free molecular residual disease (tfMRD), and single-cancer screening.

You will manage a team of bioinformatics and machine learning scientists who are building the base for the next generation of cfDNA assays.

The role suits a hands-on scientific leader who sets technical direction, reviews models and analyses closely, and prototypes when needed. You bring deep bioinformatics and machine learning expertise and experience turning research into clinical diagnostics.

Responsibilities

• Set research roadmaps for cancer early detection with the research, product, clinical, and assay development teams.
• Lead, hire, and grow a team of machine learning and bioinformatics scientists, fostering rigor, innovation, and ownership.
• Design the computational side of studies, including cohort selection, control of confounders, and validation methods that guard against overfitting and data leakage.
• Work with molecular biology teams to design experiments that produce data able to answer the key scientific and clinical questions.
• Act as the computational expert for leadership and cross-functional partners, explaining tradeoffs, risks, and recommendations to both technical and non-technical audiences.
• Build the company's scientific standing through publications, conference talks, and intellectual property.

Requirements

• PhD in bioinformatics, computer science, statistics, or a related quantitative field.
• 10+ years of experience after your PhD in industry or academia, including 5+ years managing technical teams of 5 or more scientists.
• A proven record of building and deploying machine learning and statistical models on high-throughput sequencing data.
• Deep knowledge of next-generation sequencing (NGS) data and large genomic datasets, including technical bias and batch effects.
• Strong communication skills and experience shaping scientific direction at a senior level.
• Optional: experience in clinical diagnostics, including work on assays that reached analytical or clinical validation.
• Optional: domain expertise in oncology, epigenomics, or cfDNA/liquid biopsy.
• Optional: publications or patents in computational oncology or machine learning.

Conditions

The pay range is a good-faith estimate of base pay expected at hire, $228,600 - $285,800 USD. Final pay depends on experience, qualifications, and internal equity.

The role is also eligible for the Total Rewards program: annual performance bonus, long-term equity awards, medical, dental, and vision coverage, a 401(k) with company match, generous paid time off and company holidays, and additional wellness and work-life benefits.

The company is an equal opportunity employer that welcomes candidates from all backgrounds and experiences.

Benefits

• Life and disability plans for eligible employees and dependents, free testing and fertility care for employees and their immediate families, pregnancy and baby bonding leave, 401(k), commuter benefits, and an employee referral program.