Staff Scientist, Machine Learning (Genomics)

Natera

17h • $167,400 - $209,200 • Remote

About The Position

Natera is seeking a highly motivated Staff Machine Learning Scientist for its Data Science research team. The role involves designing and prototyping algorithms for genetic and clinical data, performing data analysis and algorithm design, contributing to intellectual property, and working with R&D and product teams to define requirements and improve products and processes.

This is an individual-contributor role with Staff-level scope. The scientist will lead research on machine learning and deep learning models using next-generation sequencing (NGS) data; set technical direction; design, build, and benchmark models and features for Women Health and Organ Health products; and apply statistical learning and deep learning to high-dimensional, noisy, and often small-sample sequencing data. The role also requires working directly with sequencing pipelines, diagnosing unexpected results across pipeline, data, and biological sources, and building or extending pipeline components as needed.

The scientist will partner with molecular biology and assay development teams on experiment design and troubleshooting; establish rigorous validation, performance estimation, and documentation practices; contribute to invention disclosures, patents, publications, and presentations; and mentor data scientists and bioinformaticians. AI tools, including coding agents, are routinely used, and the role owner is responsible for the work delivered. The position is remote in the USA.

Requirements

• M.S. or Ph.D. in a quantitative field such as Computer Science, Applied Mathematics, Statistics, Bioinformatics, Computational Biology, Engineering, or a similar field; equivalent depth gained through work is accepted.
• At least 6 years of hands-on experience in machine learning and data analysis on biological or genomic data after the degree; relevant experience is counted from when work became substantially independent.
• Demonstrated record of leading models or algorithms that reached real-world use, such as a product, production pipeline, or decision-making process.
• Depth in NGS data analysis, including sequencing quality control, alignment and quantification, normalization, and sequencing artifacts.
• Working fluency with NGS bioinformatics pipelines, including running them independently, reading code and logs, tracing results through processing steps, diagnosing failures or unexpected outputs, and building or modifying components when needed.
• Extensive practical experience with machine learning, deep learning, and statistics, including model validation and performance estimation on limited or imbalanced data.
• Advanced Python skills and experience with open-source machine learning libraries such as scikit-learn, PyTorch, TensorFlow, or XGBoost in a cloud environment.
• Experience processing large datasets and working with a query language such as SQL.
• Ability to apply mathematical and statistical principles to real estimation problems and develop practical solutions.
• Familiarity with assay development and analysis pipelines for molecular or clinical biomarkers.
• Ability to communicate technical results clearly to people outside the candidate's technical background.
• Record of delivering complex projects with cross-functional teams.

Nice To Haves

• Experience with RNA-seq and small RNA/miRNA.
• Experience building probabilistic models for NGS and omics data.
• Experience with diagnostic product development in a regulated or CLIA/CAP setting.
• Experience with workflow orchestration tools such as Nextflow, WDL, or Snakemake and containerization tools such as Docker, sufficient to read, debug, and extend existing workflows.
• Experience with AWS or GCP for large-scale machine learning training and inference.
• Patents, peer-reviewed publications, or conference presentations.
• Desire to work in a fast-paced environment where a small team has high impact.

Responsibilities

• Lead research on machine learning and deep learning models using NGS data, framing problems, selecting approaches, and determining when work merits further investment.
• Set technical direction for modeling work as an individual contributor with Staff-level scope.
• Design, build, and benchmark models and features for Women Health and Organ Health products.
• Apply statistical learning and deep learning to high-dimensional, noisy, and often small-sample sequencing data, using appropriately simple methods when suitable.
• Work directly with sequencing pipelines and outputs; trace unexpected results through processing steps and diagnose whether causes relate to pipelines, data, or biology.
• Build or extend bioinformatics pipeline components when needed.
• Partner with molecular biology and assay development scientists to design experiments, including data generation, sample quantity, and controls.
• Troubleshoot experiments with laboratory teams and distinguish biological problems from data or analysis problems.
• Establish rigorous analysis practices, including sound validation design, honest performance estimates, prevention of training/evaluation leakage, and documentation.
• Support production of high-quality technical and design documentation.
• Contribute to Natera's intellectual property through invention disclosures and patent work, and to scientific publications and presentations where appropriate.
• Mentor data scientists and bioinformaticians, review their work, and advise on challenging modeling questions.
• Make method decisions with minimal direction, including in ambiguous situations, and escalate when appropriate.
• Use AI tools, including coding agents, where useful, and take ownership of the work delivered.

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior