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This is an exciting opportunity at Natera (a global leader in precision medicine and genomics testing), to oversee the entire operations of our Extended-Hours Support (ExHS) team, to provide key data analytics services for our lab production operations.  As the Director of Operations for ExHS at our Data Science Production Engineering (DSPE) department, you will have the opportunity to work with Natera's diverse and ultra-large data sets (up to PB size), apply innovative solutions built with the latest information and cloud technologies, directly support the most cutting-edge medical diagnostics and genomics applications, and make real & immediate impact to patients and healthcare providers, by ensuring the ExHS team's timely and accurate data analytics support to production teams, e.g., product management team, lab operations teams, lab director teams, and genetic counselor teams.

Important Note: This Director needs to be available during the extended hours (e.g., early morning, late evening, and weekend hours) for emergencies or other similar critical events (note: this position does not require general availability during the extended hours, but only during emergencies or other similar critical events during the extended hours).

PRIMARY RESPONSIBILITIES:

Team Leadership and Operations

• Direct and mentor a team of 10+ ExHS data science support engineers and analysts providing coverage across standard and extended operational shifts, for the timely and accurate data analytics support for production teams.
• Enforce operating procedures for compliance, quality, and efficiency.
• Measure, report, and continuously improve team operational effectiveness.
• Lead the team during critical production incidents or emergency events during and outside standard business hours.

Technical Execution and Infrastructure

• Develop and maintain technologies for operational visibility (e.g., via AWS QuickSight or Streamlit).
• Develop and maintain technologies for operational efficiency.
• Manage and execute analytics workflows on Snowflake and AWS infrastructure (Redshift, Athena, Batch, EC2, S3), and ensure strictly compliance to CLIA, FDA, and internal quality management standards.

Process Improvement

• Improve operating procedures for compliance, quality, and efficiency.
• Train and coach team members on new technologies, procedures, and guidelines/best practices.
• Identify areas for improvement within the DSPE ExHS team, develop improvement solutions, and/or work with DSPE teams to implement such solutions.

Cross-Functional Collaboration

• Represent the Extended-Hours Support (ExHS) teams in stakeholder meetings.
• Proactively manage stakeholder expectations.
• Establish regular stakeholder reporting mechanisms.
• Translate complex analytical results into actionable recommendations for cross-functional partners.

QUALIFICATIONS:

• Master's degree in Statistics, Data Science, Bioinformatics, Computer Science, Mathematics, or Operations Research required; Doctorate degrees are a plus.
• Minimum 8 years of relevant industry experience with a Master's degree (or minimum 4 years with a Doctorate).
• Minimum 3 years of experience operating within a highly regulated environment (CLIA and/or FDA compliant settings).
• Minimum 3 years of management experience leading medium-sized teams (e.g., of 7 to 20 engineers or analysts, or larger) in production support or operational roles.
• Working knowledge of diagnostic laboratory business processes and genomic/bioinformatics technologies.

KNOWLEDGE, SKILLS, AND ABILITIES:

• Proficient in data analysis and statistical techniques.
• Proficient in Python and SQL development.
• Hands-on experience with Snowflake platform technologies and AWS cloud analytics tooling (Redshift, Athena, Batch, EC2, S3).
• Demonstrated experience developing operational dashboards and analytical tools using AWS QuickSight, Streamlit, or equivalent platforms.
• Strong written and verbal communication skills, with a track record of building cross-functional trust and explaining technical data clearly.
• Ability to navigate operational ambiguity, establish structure where gaps exist, and resolve production bottlenecks directly.
• Good documentation practices and coding style.
• Strong integrity.
• Team player, collaborative.