Lead Scientist - LFA

This is a senior role in the core scientific team, responsible for the development and optimization of lateral flow immunoassays (LFAs) and other diagnostic tools. The ideal candidate will design and develop new and cutting edge quantitative Lateral Flow assays. They will guide project teams, design experimental strategies, oversee assay validation, and drive cross-functional integration with hardware and software engineering.

Key Responsibilities

• Lead design, development, and optimization of lateral flow immunoassays, from conceptualization to validation
• Drive assay architecture decisions including selection of biomarker targets, materials, control systems, and analytical thresholds
• Design, plan, and supervise rigorous experiments and statistical validations using clinical and control samples
• Lead a team of junior scientists and research associates; mentor in experimental methods and data interpretation
• Work closely with cross-functional teams (hardware, software, regulatory, sourcing) to define system requirements and ensure integration with detection platforms
• Oversee sourcing of biological reagents and manage collaborations with external partners for sample access and assay customization
• Prepare detailed documentation, research protocols, validation reports, and contribute to patent/IP generation

Required Qualifications and Skills

• Master’s degree or PhD in Life Sciences, Biotechnology, Biochemistry, or a related field with 3–6 years of relevant industry experience; AND
• 5+ years of direct experience in assay development and diagnostic product R&D
• Proven track record in development of clinically validated, large scale manufactured lateral flow assays; may not have been responsible for translation to manufacture, but the LFAs should have reached commercial utility at scale.
• Hands-on experience with antibody conjugation, protein purification, assay troubleshooting, and signal optimization
• Deep understanding of assay validation processes including specificity, sensitivity, precision, and reproducibility
• Strong analytical and documentation skills with a demonstrated ability to interpret complex biological data. Proficiency in statistical tools (e.g., Excel, GraphPad, R, or Python) for data modeling and experiment design
• Ability to manage cross-functional R&D projects in a fast-paced, collaborative startup environment