About The Position

Nanopath is seeking a Senior Scientist / Principal Scientist to join its Assay R&D team and lead verification and validation activities for its diagnostic platform. This highly hands-on role focuses on integrating assays onto the platform and includes defining requirements, developing protocols, conducting experiments, analyzing data statistically, and writing reports. The scientist will partner with Engineering, Quality, and Regulatory to ensure studies and documentation support design control and regulatory submissions. Nanopath is developing an in vitro diagnostics platform intended to bring rapid, high-quality diagnostic testing closer to patients and provide actionable results within a single office visit. The company is headquartered at The Engine in Kendall Square and emphasizes health equity, underserved populations, low-resource settings, and environmental and social sustainability.

Requirements

  • PhD or master’s degree in bioengineering, biomedical engineering, molecular biology, chemistry, or a related field, with 5+ years of relevant industry experience.
  • Experience with verification and validation in a regulated diagnostic product development environment.
  • Familiarity with design control, quality systems, GLP/GxP principles, or documentation practices for regulated diagnostics.
  • Experience with nucleic acid assays, biosensors, and/or microarrays.
  • Highly organized, efficient, attentive to detail, and motivated to complete tasks accurately and on time.
  • Excellent communication and presentation skills.
  • Experience in cross-functional and highly collaborative work environments.
  • Passion for Nanopath’s mission to develop a purpose-built solution for women’s health.

Responsibilities

  • Lead analytical verification and validation activities for Nanopath’s diagnostic platform, including study planning, protocol development, execution, analysis, and technical reporting.
  • Translate product requirements into verification and validation strategies, study designs, predefined acceptance criteria, and risk-based testing approaches.
  • Identify, investigate, and resolve assay and process performance issues, including unexpected results, sources of variability, and failure modes encountered during verification and validation.
  • Apply statistical methods, design of experiments, and risk assessment tools to evaluate performance, identify failure modes, and support data-driven decisions.
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