Remote Lead Bioinformatics & ML Scientist (Epigenomics)

Natera, Inc.; United States; Remote; USD 146,000 - 180,000; Full time

Job summary

Natera is seeking a Lead Bioinformatics & Machine Learning Scientist to contribute to our Bioinformatics Research and Development team, focused on Epigenomics in Oncology. The team develops machine learning methods for early cancer detection from cell-free DNA methylation data.

The ideal candidate will have a PhD and 4–8+ years in quantitative fields, with hands-on cancer genomics experience, strong ML skills, and a track record of mentoring others.

Qualifications

• PhD in a quantitative field with 4–8+ years post‑PhD experience.
• Hands‑on experience in cancer genomics or epigenomics; cfDNA methylation sequencing data a plus.
• Strong foundation in quantitative reasoning and applied machine learning; deep learning experience a plus.
• Proven track record of developing computational methods for high‑throughput sequencing data.

Responsibilities

• Drive technical workstreams from problem definition to final classifiers and downstream validation.
• Design, implement, and validate novel ML and statistical methods for cancer diagnostics.
• Establish best practices in model interpretability, uncertainty estimation, and reproducibility.
• Design robust feature engineering pipelines for cfDNA methylation and sequencing data.
• Collaborate with molecular biologists on experimental design and data quality control.
• Mentor scientists and foster a culture of innovation, collaboration, and scientific excellence.
• Lead and participate in code and design reviews.

Skills

Deep learning

Statistical analysis

Machine learning

Hypothesis-driven research

Mentoring

Education

PhD in a quantitative field

Tools

Python

Git

Linux

Nextflow

Snakemake

Cloud / HPC

Job description

Natera is seeking a Lead Bioinformatics & Machine Learning Scientist to contribute to our Bioinformatics Research and Development team, focused on Epigenomics in Oncology. The team develops machine learning methods for early cancer detection from cell-free DNA methylation data.

The ideal candidate will have a PhD and 4–8+ years in quantitative fields, with hands-on cancer genomics experience, strong ML skills, and a track record of mentoring others.