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Natera

Makes genetic tests for clinical care

Senior Data Analyst - Production Support

Data AnalysisUpdated on Nov 7
Full-timeSan Carlos, CA, USA

About the Job

Requirements

  • A master's degree in Statistics, Mathematics, Computer Science, Engineering, Bioinformatics, Operations Research, or another related field, plus a minimum of 3 years of relevant industry experience, or a bachelor's degree in a related field plus a minimum of 6 years of relevant industry experience.
  • A minimum of 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.
  • A 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 managing code and collaboration.
  • Ability to work collaboratively in a cross-functional team environment.
  • Strong interpersonal skills and integrity.

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 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 or 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 team in stakeholder meetings.
  • Effectively and correctly escalate encountered issues to other Data Science Production Engineering teams.

Desired Qualifications

  • A minimum of 2 years of experience working in a highly regulated environment, such as CLIA- or FDA-compliant settings.
  • Working knowledge of diagnostic laboratory business processes and requirements. Knowledge of molecular biology, genetics, genomics, or bioinformatics is a plus.

About the Company

Natera

Makes genetic tests for clinical care

Natera develops genetic tests for clinicians caring for people with cancer, inherited conditions, pregnancies, and organ transplants, using DNA analysis to inform medical decisions. Its portfolio includes Signatera for tracking residual cancer, Panorama for prenatal screening, and Prospera for assessing transplanted organ health. The company combines laboratory analysis with software that distinguishes DNA fragments in blood, and earns revenue mainly from diagnostic testing, alongside licensing and services for research partners. Clinicians use its portals to order tests, track samples, and review results, while patients have access to genetic information sessions. Natera was founded in 2004 and is headquartered in Austin, Texas.

Company size
5,001-10,000
Company stage
IPO
Headquarters
Austin, TX
Founded
2004

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