Data Scientist (Lab Informatics)

Profluent is currently seeking a creative, passionate, and detail-oriented Data Scientist with a focus on laboratory informatics. The candidate will work closely with experimental biologists to automate the capture, organization, and analysis of experimental data and create software that enhances productivity of scientists.

This is an excellent opportunity to shape the future of AI-driven protein design and to work cross-functionally with a diverse team of experts across machine learning, protein engineering, cell biology, and gene editing.

Responsibilities

• Provide computational support for experimental biology workflows (guide RNA design, primer design, barcoding, codon optimization, cloning)

• Write robust software that captures experimental data and streamlines it into Benchling and other relational databases

• Collaborate with scientists to create relational data models that represent experimental workflows

• Implement bioinformatics tools for analysis of NGS sequencing data

• Act as a data steward, who manages, organizes, and provides access to datasets generated across a protein engineering campaign

• Clearly document code and communicate outcomes to colleagues

Qualifications

• BS or MS in Computer Science, Bioengineering, Bioinformatics, or a related quantitative bioscience field

• 3+ years of academic or biotechnology industry research or laboratory experience

• Experience with Benchling or other laboratory information management systems (LIMS)

• Experience analyzing data from molecular biology experiments

• Fluent in Python data analysis tools (numpy, pandas, Jupyter notebook, biopython)

• Experience with Linux environments and version control (git)

• Pays attention to detail, highly organized, and excels in a fast-paced work environment

Preferences (but not required)

• Experience working with high throughput data and lab automation systems

• Experience designing relational data models and writing SQL queries (e.g. MySQL, PostgreSQL)

• Experience working with Google Cloud Platform (GCP) or other cloud-based compute services (e.g. AWS)

• Experience with at least one data analysis & visualization tool