Sr Bioinformatics Scientist

Twist Bioscience•South San Francisco, CA

16h•$135,000 - $173,000•Onsite

About The Position

Twist Bioscience is seeking a Senior Bioinformatics Scientist to join our Scientific Computing team supporting R&D across DNA Synthesis and Protein Solutions. You will develop computational methods and predictive models to understand biological and experimental data, guide product development, and improve scientific workflows. Working at the intersection of computational and experimental biology, you will partner with scientists to investigate challenging questions across sequencing, DNA synthesis, and protein characterization. Your work will include developing algorithms, testing hypotheses, evaluating new methods, and building reproducible analysis workflows. We are looking for a curious scientist with strong computational skills and sound scientific judgment who enjoys learning new biology and turning open-ended questions into actionable insights.

Requirements

Ph.D. with 3+ years, Master’s degree with 6+ years, or Bachelor’s degree with 8+ years of relevant experience in bioinformatics, computational biology, biostatistics, or a related field; equivalent combinations of education and experience will be considered.
Strong Python programming skills and experience analyzing biological or experimental data.
Hands-on experience with NGS analysis and a solid understanding of molecular biology.
Experience developing and evaluating computational algorithms, statistical methods, or predictive models.
Strong foundation in statistics, experimental design, and critical interpretation of scientific results.
Experience building reproducible analysis workflows using Nextflow or a comparable tool.
Demonstrated ability to independently investigate scientific problems and learn unfamiliar methods or biological domains.
Ability to collaborate closely with experimental scientists and communicate complex findings clearly.

Nice To Haves

Experience with protein data analysis, DNA synthesis, or sequence design.
Experience applying machine learning to biological data, including rigorous validation.
Experience working with high-throughput experimental datasets and integrating multiple data types.
Familiarity with cloud computing and scalable scientific workflows.
A track record of developing computational methods that inform experimental decisions or improve products.
We welcome candidates with depth in a relevant scientific area and the curiosity and quantitative foundation to contribute across disciplines.

Responsibilities

Develop novel computational methods and algorithms supporting DNA synthesis, sequence analysis, and protein characterization.
Partner with experimental scientists to formulate hypotheses, design experiments, and interpret results that guide product and process development.
Analyze NGS and other experimental datasets to identify biological patterns, understand sources of variability, and investigate unexpected outcomes.
Apply statistical methods, machine learning, and predictive modeling to connect sequence and experimental features with product quality and performance.
Evaluate and validate analytical approaches, including their accuracy, limitations, and applicability across experimental conditions.
Develop reproducible analysis pipelines using Nextflow and other scientific computing tools to support research and method evaluation.
Communicate findings and recommendations to scientific and cross-functional stakeholders, and collaborate with engineers to translate successful methods into broader use.
Explore new technologies and analytical approaches as research priorities evolve.