Lead Machine Learning and Bioinformatics Scientist

PhD in Computer Science, Machine Learning, Statistics, Bioinformatics, or a related quantitative field with a strong emphasis on cancer epi/genomics and 6+ years of experience post-PhD.

Deep expertise in the theory and practical development of core machine learning models, including generalized linear models, kernel methods, tree-based algorithms, and neural networks, with a focus on biological data (e.g., DNA/RNA sequencing data)

Proficiency in Python and its scientific computing stack (e.g., NumPy, Pandas, Scikit-learn)

Strong cross-functional communication skills, with the ability to collaborate effectively across disciplines

High scientific rigor and a growth mindset, with enthusiasm for both teaching and learning new computational and biological concepts

This range reflects a good-faith estimate of the base pay we reasonably expect to offer at the time of  hire. Final compensation will vary based on experience, qualifications, and internal equity considerations.

This position is also eligible for additional compensation and benefits through Natera’s robust Total Rewards program, including:

Annual performance incentive bonus

Long-term equity awards

401(k) with company match

Design, implement, and validate cutting-edge machine learning and statistical methods to solve problems in cancer diagnostics

Contribute to best practices in model interpretability, uncertainty estimation, and reproducibility

Design robust feature engineering and extraction pipelines tailored to biological data

Prototype and productionize models using scalable ML infrastructure tools such as MLflow, Airflow, and Docker

Collaborate closely with molecular biologists on experimental design, ensuring data integrity and quality control

Foster a culture of innovation, collaboration, and scientific excellence