Senior Data Analyst for Lab Production Support, Extended-Hours Support (ExHS)

Natera

6h • $130,000 - $155,000 • Remote

About The Position

This is an exciting opportunity in our Data Science Production Engineering (DSPE) department at Natera (a global leader in precision medicine and genomics testing), to provide critical data analytics support for our lab production operations. As a Senior Data Analyst for Lab Production Support in our DSPE Extended-Hours Support (ExHS) team, you will work in the Weekend Shift team (following the above two rotation schedules). You will have the opportunity to apply innovative data analytics solutions, directly support the most cutting-edge medical diagnostics and genomics applications, and make real & immediate impact to patients and healthcare providers, by providing timely & accurate data analysis support to Natera's production laboratories, as well as for other key business needs.

Requirements

• Masters degree in Statistics, Mathematics, Computer Science, Bioinformatics, Operational Research, or other related fields.
• Minimum 3 years of relevant industry experience.
• Minimum 3 years of experience working in a highly regulated environment (e.g., CLIA and/or FDA compliant settings).
• Minimum 3 years of hands-on experience in data analysis, extraction, querying in production support roles.
• Working knowledge of the business processes and requirements of diagnostic laboratories.
• Proficient in data analysis and statistical techniques.
• Proficient in Python and SQL development.
• Working knowledge of Snowflake platform and cloud technologies.
• Strong understanding of statistical concepts such as hypothesis testing, central limit theorem, time series analysis, anomaly detection, and regression modeling.
• Good documentation practices and coding style.
• Strong verbal and written communication skills, with the ability to present technical findings to both technical and non-technical audiences.
• Experience using version control systems such as GitHub or GitLab for managing code and collaboration.
• Ability to work collaboratively in a cross-functional team environment.
• Strong interpersonal skills.
• Strong integrity.

Nice To Haves

• Knowledge of molecular biology, genetics, genomics, and/or bioinformatics is a plus.

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, improving operational efficiency and scalability.
• Extract, transform, and analyze data to generate actionable insights that support lab production operations and business decisions.
• Document analytical processes, best practices, and insights to ensure consistency and knowledge transfer across teams.
• Develop and optimize solutions for efficient data retrieval and scalable performance on large and/or complex datasets.
• Learn and acquire operational efficiencies on new technologies and solutions developed by other DSPE teams.
• Train and coach junior team members on new technologies, procedures, and guidelines/best practices.
• Collaborate with Lab Operations and Product teams to identify process issues, assist with root cause analysis, and provide product support.
• Represent the Data Science Production Engineering (DSPE) team in stakeholder meetings.
• Effectively and correctly escalate encountered issues to other DSPE teams.

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.
• 401k benefits.
• Commuter benefits.

What This Job Offers

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