Principal Scientist, Computational Biology

About Stylus Medicine:

Stylus Medicine is developing transformative in vivo genetic medicines to unlock cures. Stylus combines engineered recombinases with non-viral delivery to specifically encode therapeutics. The company’s approach is versatile and modular, with potential therapeutic application across oncology, autoimmune, genetic diseases, and beyond.

About the Role:

Stylus Medicine is seeking an innovative, intellectually curious and team-oriented Principal Scientist to support our large serine recombinase (LSR) engineering platform. This individual will provide high-resolution efficacy and specificity analysis to advance our pipeline as well as support onboarding of new preclinical assays for regulatory submissions, ensure accuracy of our analysis pipelines and translate our wet lab experiments into computational insights that will enable engineering of our next generation LSRs.

Key Responsibilities & Accountabilities:

• Lead the analysis of NGS data from LSR experiments (like amplicon, hybrid capture, and long-read sequencing) to quantify target efficiency and specificity


• Build integrated workflows to annotate and characterize target sites by synthesizing proprietary datasets with large-scale public genomic databases


• Design, implement, and scale robust computational pipelines for multi-omics analysis


• Collaborate closely with the Screening, Genome Engineering, and Protein Engineering teams to design experiments and interpret results


• Develop and maintain internal databases and infrastructure to ensure experimental results are accessible, reproducible, and actionable


• Contribute to patent filings, regulatory submissions, and scientific publications

Qualifications & Skills:

• PhD with 5+ years or Master’s with 10+ years (or Bachelor’s with 12+ years) of industry experience in Computational Biology, Bioinformatics, or a related quantitative discipline.


• Strong expertise in experimental design, data processing, statistical analysis, and NGS data analysis


• Expert-level proficiency in Python and/or R, with extensive experience using data science libraries (e.g., Pandas, NumPy, Bioconductor)


• Experience with cloud computing platforms for large-scale data processing and with workflow management systems


• Excellent organizational, communication, and documentation skills, with demonstrated ability to work effectively in collaborative, interdisciplinary environments


• Strong scientific critical thinking skills, including the ability to evaluate approaches, synthesize complex data, and provide actionable recommendations


• Proven track record of working successfully across cross-functional teams with proactive communication and timely delivery

Pay Range: $180,000 - $195,000