Profluent Lead Scientist to design, develop, and operate the NGS analysis platform for gene editing and protein design. Lead computational characterization and mentor a bioinformatics and data science team.
Responsibilities
Lead the development and operation of Profluent’s NGS analysis platform for gene editing, protein design, and therapeutic programs
Develop scalable pipelines and analytical methods for new sequencing assays
Partner with wet-lab teams to design, test, troubleshoot, and validate new assays
Lead computational characterization of gene-editor on-target activity, specificity, and off-target effects
Translate sequencing data into clear biological insights, program decisions, and regulatory-ready analyses
Collaborate with computational teams to curate high-quality datasets for model training and evaluation
Establish rigorous, reproducible practices for analytical validation, testing, documentation, and code review
Recruit, mentor, and develop a high-performing bioinformatics and data science team
Qualification
PhD or MS in BioinformaticsDeep expertise in the designDemonstrated scientific leadershipExperience developing scalableExperience with LIMS platforms (e
Required
PhD or MS in Bioinformatics, Computational Biology, Computer Science, or a related quantitative field
PhD with 5+ years or MS with 7+ years of industry experience applying NGS and computational analysis to gene or cell therapy development
Deep expertise in the design, analysis, and interpretation of high-throughput sequencing assays
Strong programming and quantitative analysis skills, particularly in Python
Proven ability to translate complex sequencing data into clear biological insights and program decisions
Experience partnering closely with experimental scientists to guide assay design, troubleshoot results, and define follow-up studies
Demonstrated scientific leadership, including setting analytical strategy, leading complex cross-functional projects, and mentoring computational scientists
Experience developing scalable, reproducible, and well-validated computational workflows
Experience with CRISPR-based gene editing data and analysis
Familiarity with SQL and data modeling for biological or experimental data
Experience with LIMS platforms (e.g., Benchling) and lab data integration
Track record of developing production-quality scientific software and tools
