Lead Bioinformatics, Machine Learning Scientist

Natera

. Develop, train, and evaluate machine learning models for cancer detection in the minimal residual disease setting .

Posted 11/4/2026full-timeRemote • United StatesSenior💰 $146,000 - $182,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in developing and evaluating machine learning models for cancer detection, with a strong foundation in high-throughput DNA sequence data analysis and algorithm development. Proficient in translating experimental design into computational analysis while maintaining rigorous quality control and effective communication with cross-functional teams.

Highest-signal resume keywords

PhD In Computer ScienceMachine Learning Model DevelopmentHigh-Throughput DNA Sequence Data AnalysisPython ProgrammingAlgorithm Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningStatistical MethodsData AnalysisSequence AlignmentVariant CallingGeneralized Linear ModelsKernel MethodsTree-Based AlgorithmsNeural NetworksQuantitative Reasoning

Soft Skills

CommunicationCollaborationEagerness To LearnScientific Rigor

Tools & Technologies

PythonLinux Command-Line ToolsNumPyMatplotlibPandasTCGACOSMICOncoKB

Industry Keywords

Cancer DetectionBioinformaticsComputational BiologyCancer Epi/GenomicsQuality ControlCross-Functional Teamwork

Tech Stack

Tools & technologies

LinuxNumpyPandasPython

About the role

Key responsibilities & impact

Develop, train, and evaluate machine learning models for cancer detection in the minimal residual disease setting
Drive algorithm design decisions supporting cancer detection
Own end-to-end research analyses from ideation through implementation, troubleshooting, and performance evaluation
Develop new features within existing pipelines
Translate between wet-lab experimental design and computational analysis
Maintain rigorous quality control across high-volume sequencing data spanning multiple cohorts, vendors, and clinical protocols
Communicate findings and model performance to technical and cross-functional stakeholders
Contribute to standards for code quality and reproducibility

Requirements

What you’ll need

PhD in Computer Science, Bioinformatics, Computational Biology, or a related quantitative field with a strong emphasis on cancer epi/genomics
4 to 8+ years of experience post-PhD
Deep theoretical and practical understanding of high-throughput DNA sequence data analysis, including mapping, sequence alignment, and variant calling workflows
Experience in algorithm development and data analysis, including applying and evaluating statistical methods
Demonstrated experience developing core machine learning models, including generalized linear models, kernel methods, tree-based algorithms, and neural networks, focused on biological data
Strong quantitative reasoning and data analysis skills
Experience with Python and Linux command-line tools, including writing shell scripts
Strong computational and programming skills, including thorough experience with Python statistical packages such as NumPy, Matplotlib, and Pandas
Familiarity with public databases such as TCGA, COSMIC, or OncoKB
Ability to visualize findings and summarize results for technical and non-technical audiences
High scientific rigor and eagerness to learn new computational methods and biology
Ability to work on a cross-functional team with computational and experimental scientists

Benefits

Comp & perks

Comprehensive medical, dental, vision, life and disability plans for eligible employees and dependents
Free testing for Natera employees and their immediate families
Fertility care benefits
Pregnancy and baby bonding leave
401(k) benefits
Commuter benefits
Employee referral program