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Natera

Makes genetic tests for clinical care

Data Science Manager

Data ScienceConfirmed live in the last 24 hours
Full-timeSan Carlos, CA, USAIn-person

About the Job

Requirements

  • At least 7 years of experience in data science in biotechnology, life sciences, or operations research.
  • Demonstrated people-management experience, including hiring, mentoring, and developing data scientists through coaching on performance and career growth.
  • Experience owning a data science roadmap and communicating progress to senior and executive stakeholders.
  • Working knowledge of a relevant scientific or operational domain, such as biology, life sciences, or operations research, sufficient to partner effectively with R&D Operations stakeholders.
  • Experience working with laboratory or operational data, such as a laboratory informatics management system, sample management, inventory, purchasing or procurement, or equipment operations.
  • A track record of driving process improvement by identifying root causes and delivering solutions through process changes, algorithms, or new tools.
  • A strong background in building data processes, standard operating procedures, and governance frameworks.
  • Expertise in Python, including pandas, scikit-learn, TensorFlow or PyTorch, and SQL.
  • Hands-on expertise in machine learning or artificial intelligence applied to real-world problems, including setting technical direction for predictive modeling and optimization solutions.
  • Experience taking machine learning models or data products from prototype to production, including monitoring and maintenance.
  • Experience with modern cloud data warehouse and transformation tooling, such as Snowflake and dbt.
  • Experience partnering with peer functions such as engineering and analytics to deliver end-to-end solutions, including writing requirements or technical specifications.
  • Clear, direct communication skills to translate complex data insights into actionable business recommendations.
  • Strong critical thinking and a drive for learning and problem-solving.

Responsibilities

  • Direct, mentor, and develop a team of data scientists, including hiring, performance management, and career development.
  • Set the technical direction for the data science team and advance its machine learning and artificial intelligence capabilities.
  • Own the data science roadmap for R&D Operations, define success metrics, and report progress and status to R&D Operations and executive stakeholders.
  • Translate pain points and opportunities surfaced by data analytics into solutions, such as process changes, algorithms, or new tools, and drive their implementation to deliver measurable process improvement, including efficiency gains in turnaround time and cost per activity across R&D Operations.
  • Own the sample governance process end-to-end, ensuring accuracy, timeliness, and accountability, and manage the associated stakeholder relationships.
  • Develop and oversee machine learning models, optimization strategies, and artificial intelligence solutions to forecast demand, optimize resource allocation, and automate operational processes.
  • Lead development of new data products and their training and enablement to grow visibility, self-service, and data-driven decision-making across R&D Operations.
  • Design, document, and implement processes for data governance, data integrity, and reproducibility across R&D Operations.
  • Partner with the Data Engineering and Data Analytics Managers and collaborate cross-functionally across R&D and supporting functions to translate business needs into governed, reliable data solutions.
  • Write clear, testable requirements, such as acceptance criteria and data contracts, and define the path from prototype to production in partnership with Data Engineering.

Desired Qualifications

  • An advanced degree in biology, molecular biology, biochemistry, bioinformatics, or operations research.
  • Familiarity with data integrity and audit-readiness practices in a regulated GxP or GCLP environment.

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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