Senior Data Analyst, Production Support

Natera•San Carlos, CA

8d•$145,000 - $170,000

About The Position

This is an opportunity in Natera’s Data Science Production Engineering (DSPE) department to provide critical data analytics support for lab production operations. As a Senior Data Analyst for Lab Production Support on the DSPE Extended-Hours Support (ExHS) team, you will support Natera’s production laboratories and other business needs with timely, accurate data analysis. The work applies data analytics to medical diagnostics and genomics operations, helping resolve production issues and improve patient-results turnaround times. The position is part of the Weekend Shift team and alternates quarterly between two 9 AM–5 PM schedules: Tuesday through Saturday and Sunday through Thursday. The role applies statistical and analytical methods, develops automated workflows, improves data retrieval and scalability, documents processes, and collaborates with Lab Operations, Product, and other DSPE teams.

Requirements

At least 3 years of relevant industry experience with a master’s degree in Statistics, Mathematics, Computer Science, Engineering, Bioinformatics, Operational Research, or a related field; alternatively, at least 6 years of relevant industry experience with a bachelor’s degree in a related field.
At least 3 years of hands-on experience in data analysis, extraction, and querying.
Proficiency in data analysis and statistical techniques.
Proficiency in Python and SQL development.
Working knowledge of the Snowflake platform and cloud technologies.
Strong understanding of statistical concepts, including hypothesis testing, the central limit theorem, time-series analysis, anomaly detection, and regression modeling.
Good documentation practices and coding style.
Strong verbal and written communication skills, including the ability to present technical findings to technical and non-technical audiences.
Experience using version control systems such as GitHub or GitLab for code management and collaboration.
Ability to work collaboratively in a cross-functional team environment.
Strong interpersonal skills and integrity.
Ability to work the rotating Weekend Shift schedules: Tuesday–Saturday or Sunday–Thursday, 9 AM–5 PM, alternating quarterly.

Nice To Haves

At least 2 years of experience working in a highly regulated environment, such as a CLIA- and/or FDA-compliant setting (preferred but not required).
Working knowledge of diagnostic laboratory business processes and requirements.
Knowledge of molecular biology, genetics, genomics, and/or bioinformatics.

Responsibilities

Deliver timely data support to Lab Operations teams, unblock production issues, and improve patient-results turnaround times.
Apply statistical techniques to analyze complex datasets, diagnose operational issues, and support data-driven decision-making.
Perform exploratory data analysis, identify trends, and work with stakeholders to interpret findings and drive continuous improvement.
Design and implement automated solutions for recurring data analysis and production-support workflows to improve operational efficiency and scalability.
Extract, transform, and analyze data to generate actionable insights for lab production operations and business decisions.
Document analytical processes, best practices, and insights to support consistency and knowledge transfer across teams.
Develop and optimize solutions for efficient data retrieval and scalable performance on large or complex datasets.
Learn operational efficiencies and technologies developed by other DSPE teams.
Train and coach junior team members on technologies, procedures, guidelines, and best practices.
Collaborate with Lab Operations and Product teams to identify process issues, assist with root-cause analysis, and provide product support.
Represent the DSPE team in stakeholder meetings.
Escalate encountered issues appropriately to other DSPE teams.