Lead Bioinformatics, Machine Learning Scientist – Epigenomics

Natera

. Drive technical workstreams from problem definition through delivery of final classifiers to downstream validation teams .

Posted 11/5/2026full-timeRemote • United StatesSenior💰 $146,000 - $180,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in developing and validating machine learning methods for cancer diagnostics, with a strong foundation in statistical analysis and quantitative reasoning. Proven ability to mentor scientists and collaborate effectively in a multidisciplinary environment.

Highest-signal resume keywords

PhD In BioinformaticsCancer Genomics ExperienceApplied Machine LearningPython ProgrammingStatistical Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning MethodsStatistical AnalysisFeature EngineeringData Extraction PipelinesHigh-Throughput Sequencing AnalysisModel InterpretabilityUncertainty EstimationReproducibility PracticesHypothesis-Driven ResearchData Visualization

Soft Skills

MentoringCollaborationScientific ExcellenceCommunication

Tools & Technologies

Linux Command-Line ToolsGitNextflowSnakemakeCloud ComputingHPC EnvironmentsPython Scientific Libraries

Industry Keywords

Cancer DiagnosticsCfDNA MethylationEpigenomicsQuantitative ReasoningData IntegrityQuality Control

Tech Stack

Tools & technologies

CloudLinuxNumpyPandasPythonScikit-LearnShell Scripting

About the role

Key responsibilities & impact

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 best practices in model interpretability, uncertainty estimation, and reproducibility
Design feature engineering and extraction pipelines for cfDNA methylation and sequencing data
Collaborate with molecular biologists on experimental design, data integrity, and quality control
Mentor scientists and foster innovation, collaboration, and scientific excellence
Lead and participate in code and design reviews

Requirements

What you’ll need

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 of developing computational methods for high-throughput sequencing data analysis
Strong programming skills with hands-on experience in Python and its scientific library stack: 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 summarize results orally and in writing
Experience mentoring or technically leading other scientists

Benefits

Comp & perks

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
401k benefits
Commuter benefits
Employee referral program