Lead Bioinformatics & Machine Learning Scientist (Epigenomics)
About The Position
Natera is seeking a Lead Bioinformatics & Machine Learning Scientist to contribute to research and development within its Bioinformatics Research and Development team, focused on epigenomics in oncology. The team develops machine learning methods for early cancer detection using cell-free DNA methylation data. The role will help develop and expand state-of-the-art machine learning methods for early cancer detection and provide technical leadership and mentorship within a collaborative team. The position drives methods from problem definition through delivery of final classifiers to downstream validation teams. It involves developing and validating machine learning and statistical methods, building feature engineering and extraction pipelines for cfDNA methylation and sequencing data, and working with molecular biologists on experimental design and data quality. The role is remote in the USA.
Requirements
- PhD in Bioinformatics, Computer Science, Machine Learning, Statistics, or a related quantitative field.
- 4 to 8+ years of post-PhD experience.
- Hands-on experience in cancer genomics or epigenomics.
- Strong foundation in quantitative reasoning, statistical analysis, and applied machine learning.
- Proven track record developing computational methods for high-throughput sequencing data analysis.
- Strong programming skills, including hands-on experience with Python and its scientific library stack, such as pandas, NumPy, and scikit-learn.
- Experience with Linux command-line tools, shell scripting, Git, workflow managers such as Nextflow or Snakemake, and cloud or HPC compute environments.
- Ability to perform hypothesis-driven research, visualize findings, and communicate results orally and in writing.
- Experience mentoring or technically leading other scientists.
Nice To Haves
- Experience with cell-free DNA or methylation sequencing data.
- Experience with deep learning frameworks.
Responsibilities
- Drive technical workstreams from problem definition through delivery of final classifiers to downstream validation teams.
- Design, implement, and validate novel machine learning and statistical methods for cancer diagnostics.
- Establish and promote best practices in model interpretability, uncertainty estimation, and reproducibility.
- Design robust feature engineering and extraction pipelines tailored to cfDNA methylation and sequencing data.
- Collaborate with molecular biologists on experimental design, data integrity, and quality control.
- Mentor other scientists and foster innovation, collaboration, and scientific excellence.
- Lead and participate in code and design reviews.
Benefits
- Comprehensive medical, dental, vision, life, and disability plans for eligible employees and their dependents.
- Free testing for employees and their immediate families.
- Fertility care benefits.
- Pregnancy and baby bonding leave.
- 401(k) benefits.
- Commuter benefits.
- Employee referral program.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
