Senior Development Scientist I

At Freenome, we are seeking a Senior Development Scientist I to help grow the Freenome Genomics Late Development team. You will develop, optimize, verify, and validate clinical-grade assay technologies for Freenome's multiomic platform, advancing our mission to detect cancer earlier. Working across manual and automated workflows, you will collaborate with cross-functional teams to develop and transfer robust NGS-based assays into a regulated, high-throughput production environment. You are passionate about developing life saving diagnostics using NGS technologies, and you will have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer.

The role reports to the Senior Manager of Genomics Development. This role will be an onsite role based in our Brisbane, California headquarters.

• →Apply knowledge of molecular biology, nucleic-acid biochemistry, and next-generation sequencing to develop assays for DNA, including genome-wide and targeted approaches.
  
• →Oversee and lead mission-critical experiments to optimize, characterize, verify, and validate NGS-based assays, owning scientific strategy, experimental design, planning, timelines, execution, and delivery.
  
• →Design and execute high-impact experiments, generate detailed documentation, perform data analysis, create summary presentations, and present results cross-functionally.
  
• →Troubleshoot complex technical challenges, identify root causes, and drive process improvements to assay performance and laboratory workflows.
  
• →Drive project planning and prioritization by defining milestones, identifying and mitigating risks, and adapting to evolving program needs.
  
• →Build productive working relationships and partner cross-functionally with computational scientists, engineers, and clinical laboratory team members to transition development protocols into clinical production, including automation, validation experiments, and SOP development.
  
• →Document product development requirements and author study protocols and reports. Diligently apply current Good Laboratory and Documentation Practices (cGLP, cGDP) to maintain high standard of scientific rigor and quality.
  

• PhD in molecular biology, biochemistry, genetics, or a related field with at least 4 years of professional experience in the life sciences, or a Bachelors or Masters degree with at least 10 years of professional experience. Prior experience in clinical diagnostics and/or working in a start-up environment is preferred.
  
• Experience designing and leading the execution of verification and validation studies for IVD assays in a regulated clinical laboratory environment (GLP).
  
• Extensive hands-on experience in Next-gen sequencing (NGS) based automated assay development including extraction, library preparation, target capture, and sequencing. Experience working with automated platforms and liquid handlers.
  
• Extensive hands-on experience in nucleic acid preparation, amplification, and quantification (DNA/RNA extraction and purification, PCR, qPCR, Qubit, Fragment Analyzer, Tapestation). Experience in working with ctDNA/cfDNA as an analyte in NGS workflows.
  
• Proven track record of designing, planning, and executing successful experiments, including performing independent data analysis and giving effective scientific presentations.
  
• High attention to detail and ability to record accurate and detailed observations, assess impact, and lead independent troubleshooting investigations.
  
• Excellent written and verbal communication. Proactive communicator with ability to foster collaboration in a multidisciplinary team. 
  
• Flexible and highly motivated to learn new skills and comfortable adapting to changing priorities.
  
• Experience providing technical mentorship and training to other scientists and research associates to contribute to a culture of technical excellence and continuous improvement.
  

• Experience in working with with methylated ctDNA/cfDNA as an analyte in NGS workflows.
• Familiarity with scientific programming or data analysis tools such as Python or R, and experience contributing to publications, patents, or other scientific innovations.