Manager of Bioinformatics (Women's Health and Organ Health)

Natera is seeking a Manager, Bioinformatics to lead production support for the bioinformatics and data science algorithms behind our Women's Health and Organ Health products.

About the Role

You will lead a team of Data and Bioinformatics Scientists who are accountable for how those algorithms behave on real samples, and you will own the interface between that team and the production organization. The key challenge of this role is resolving inconclusive reports, where a scientist has to weigh the full body of evidence to reach a determination. You will determine whether an inconclusive report reflects technical constraints or a data quality issue, and how the upstream processes should change so that fewer cases arrive inconclusive. You will maintain a catalogue of known patterns so that new cases can be matched to settled ones, and use AI to assemble and help interpret the evidence at triage.

The job is more than operational, and it is the most cross-functional seat on the team. You’ll need to coordinate across multiple groups – Production Engineering, Product, the laboratory, and R&D – often getting them to align on changes in direction and scope, so success requires leveraging strong communication, negotiation, and consensus-building skills rather than authority. There is no stated service commitment for this function yet, and defining one is part of the job. You will work out what the team can commit to on turnaround and coverage, get the groups that depend on it to agree, and build the process and staffing that hold it.

AI is a routine part of the work here. Support is one of the places where these tools help most and where an unreviewed conclusion does the most damage, so you set the standard: what an agent may conclude on its own, and what has to be reproduced by hand before it goes in a record. We do not screen for prior experience with these tools, and many strong candidates come from environments where they were restricted; we provide the tooling and the ramp time.

Responsibilities

• Own the support function for our data science and bioinformatics algorithms in production, ensuring answers are right and arrive when they are still useful.
• Lead complex investigations that cross system boundaries, distinguishing biological signal problems from algorithm, data, or infrastructure issues, and identifying the group responsible for the fix.
• Turn one-off investigations into durable rules and design changes to prevent recurring issues.
• Own process validation for pipelines and algorithms as operations change, defining evidence requirements before changes go live and maintaining standards under schedule pressure.
• Lead, hire, and grow a team of Data and Bioinformatics Scientists, demonstrating deep systems judgment.
• Partner with Production Engineering, Product, Bio Development, laboratory operations, and Data Science R&D teams to resolve and prevent operational issues.
• Represent algorithm capabilities to dependent groups, negotiating commitments and upstream fixes requiring their agreement.
• Set standards for AI-assisted investigations, determining what conclusions require manual review before being recorded.

What Success Looks Like After a Year

• Recurring escalations are fewer, and test turnaround time (TAT) is reduced. You can identify which recurring issues were eliminated and how, including upstream fixes and feature requests that stopped them from recurring.
• A service commitment for the function exists, agreed upon with dependent groups, and the team consistently meets it.
• Change validation is a defined, repeatable process the team follows, not an ad-hoc judgment.
• Your scientists handle investigations independently that previously required your intervention.
• The production organization relies on your team for answers, not just for routing inquiries to other groups. The team can resolve inconclusive reports without escalation.
• Agent-assisted investigation is standard on the team, with a clear standard you established.

Qualifications

• M.S. or Ph.D. in Bioinformatics, Computational Biology, Data Science, or a related technical field. Equivalent work experience is fully considered.
• 5+ years working with genomic or sequencing data, including 2+ years leading people. Relevant experience is counted from when your work became substantially independent.
• Demonstrated ownership of a support, escalation, or on-call function with defined commitments, in a setting where errors had consequences.
• Experience leading cross-system investigations to resolution, including knowing when to stop.
• Proven ability to reach agreement across organizational lines without authority, such as adopting a standard, resolving competing priorities, or persuading others to adopt a position.

Skills and Abilities

• Sequencing and bioinformatics fluency to distinguish real pipeline failures from expected outcomes and challenge plausible-but-incorrect results.
• Ability to reconstruct events from logs, intermediate files, and pipeline outputs by working directly with the data.
• Proficiency in Python and SQL for investigations, including pulling records, comparing runs, and building small tools to avoid redundant work.
• Experience working within change control, including validation and documentation practices that withstand post-hoc review.
• Experience defining a support process, including setting commitments, securing agreement from dependent groups, and staffing to meet those commitments.
• People leadership demonstrated through specific outcomes: expanding someone’s scope, successful hires, or managing someone out of the wrong role into a better fit.
• Understanding of laboratory operations to recognize when data issues originate upstream of your responsibilities.
• Cross-functional relationships that enable technical or operational escalations to start as conversations rather than tickets.
• Senior-level communication, negotiation, and persuasion skills: tailoring explanations for engineers, laboratory directors, and executives, and driving decisions under pressure.

Strong candidates may also have:

• Machine learning or statistical analysis experience applied to genomic data.
• Experience with cell-free DNA, prenatal, or carrier screening applications.
• Experience in an accredited or high-complexity laboratory setting, or familiarity with regulated diagnostic practices and standards.
• Familiarity with workflow systems such as WDL, Nextflow, Snakemake, or Cromwell.
• Experience building observability or alerting systems that detected problems before customers did.

Benefits

• Annual performance incentive bonus
• Long-term equity awards
• Comprehensive health benefits (medical, dental, vision)
• 401(k) with company match
• Generous paid time off and company holidays
• Additional wellness and work-life benefits
• Free testing for employees and their immediate families, plus fertility care benefits
• Pregnancy and baby bonding leave
• Commuter benefits
• Generous employee referral program

Pay

Compensation range: $154,000—$192,500 USD. 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.