Scientist I

Guardant Health•Redwood City, CA

56d•$115,200 - $158,400•Hybrid

About The Position

The Technology Development Department is responsible for developing, validating, implementing, and maintaining the tests used by Guardant Health for cancer detection. This role sits in Sustain & Support (S&S) within Technology Development, partnering tightly with Clinical Operations to triage and resolve clinical failures, develop and improve reagent QC systems to reduce recurring failures, and optimize on-market liquid and tissue assays under regulated quality systems. Within S&S, we optimize deployed methods when quality issues arise, develop PQ strategies, scale manufacturing processes, and drive sustaining projects under design control. This team operates at the intersection of assay, bioinformatics, operations, and quality, serving as the link across functions to sustain robust clinical production. The Scientist I in S&S will help ensure the reliability and continuous improvement of Guardant’s on-market assays. This role will focus on investigating and resolving failures in clinical laboratory operations, strengthening reagent QC systems to improve consistency and reduce repeat issues, and supporting process validations in compliance with regulated quality systems. The Scientist I will combine wet-lab assay expertise, laboratory and operational data analysis, and structured quality-system investigation to identify root causes, guide corrective actions, and enhance product performance. They will work closely with Clinical Operations, Bioinformatics, Process Engineering, Reagent QC, Manufacturing, and Quality teams to deliver durable fixes, reduce QC failures, and enable efficient technology transfer into production. In addition, the scientist will contribute to NCR and other quality-system investigations, support validation and change-control documentation, and provide ongoing technical support for sustaining and scaling Guardant’s assays.

Requirements

PhD in Molecular Biology, Genomics, Biochemistry or related field, or equivalent work experience.
A minimum of 0-2 of related experience (post-doctoral research or relevant industry experience will be considered)
Strong foundation in molecular biology, including experience with NGS library preparation and target enrichment. Familiarity with circulating cell-free nucleic acid workflows is a plus.
Experience operating NGS instruments and executing sample-preparation assays in medium- or high-throughput environments. Experience with process automation or liquid-handling platforms is preferred but not required.
Strong data-analysis skills using Python and Jupyter for scripting, automation, and visualization, with the ability to work across SQL tables, flat files, LIMS, and other laboratory data sources. Experience analyzing assay, reagent QC, operational, or sequencing datasets is strongly preferred. Familiarity with NGS bioinformatics outputs is an advantage.
Experience designing, executing, or analyzing structured scientific studies, with strong technical documentation and report-writing skills. Experience with verification, validation, manufacturing process studies, or SOP/Work Instruction authorship is preferred.
Excellent cross‑discipline communication and a track record of independent and team‑based problem solving in fast‑paced environments.
Strong organization, attention to detail, and commitment to good documentation practices (GDP).
Experience working under structured laboratory or quality-system requirements, with an understanding of controlled documentation, traceability, deviation investigation, and change management. Experience in FDA-, CLIA-, or ISO 13485-regulated environments is preferred.
Demonstrate curiosity, sound judgment, and the ability to critically evaluate and responsibly leverage AI-enabled tools in accordance with company policies, ethical standards, and regulatory requirements to improve the efficiency, effectiveness, and quality of work.

Nice To Haves

Familiarity with circulating cell-free nucleic acid workflows is a plus.
Experience with process automation or liquid-handling platforms is preferred but not required.
Experience analyzing assay, reagent QC, operational, or sequencing datasets is strongly preferred.
Familiarity with NGS bioinformatics outputs is an advantage.
Experience with verification, validation, manufacturing process studies, or SOP/Work Instruction authorship is preferred.
Experience in FDA-, CLIA-, or ISO 13485-regulated environments is preferred.

Responsibilities

Draft and execute verification and validation protocols, including IQ/OQ/PQ activities; contribute to design- and change-control packages and risk assessments; and support manufacturing process validation activities to production-grade standards.
Operate and troubleshoot NGS workflows end to end, including sample preparation, library preparation, target enrichment, sequencing, and medium- to high-throughput runs. Operate laboratory automation platforms as applicable and support instrument maintenance, troubleshooting, and defined method improvements.
Partner with Technology Development and Bioinformatics to develop, evaluate, and implement assay and process improvements; execute structured transfers into Clinical Operations; and support the clinical laboratory post-transfer through troubleshooting, training, and controlled documentation.
Analyze assay, reagent QC, sequencing, and clinical operations data by integrating information from SQL databases, flat files, LIMS, and other internal data sources. Use Python and Jupyter to identify trends, test hypotheses, and determine relationships between upstream process variables, QC metrics, and assay failures.
Follow FDA and ISO 13485 quality-system standards and support structured investigations of assay, reagent, and process failures, including root-cause analysis, impact assessment, evaluation of potential corrective actions, and preparation of supporting documentation for NCRs, change controls, audit responses, and related quality records. Maintain complete, GDP-compliant records with full traceability.
Present technical findings, conclusions, limitations, and risk–benefit tradeoffs to laboratory leadership, Bioinformatics, Process and Manufacturing Engineering, and Clinical Operations; write clear technical reports; and support cross-functional decision-making.