Director, Data Science

Responsibilities

• Technical Leadership
• Set the technical direction for ML model development: amino acid classification from nanopore current signals, signal segmentation, stall detection, temporal modeling, and multi-cycle analysis.
• Drive improvements to classification accuracy through better architectures (transformers, deep learning), training strategies, and feature engineering.
• Own the roadmap for data infrastructure: pipeline automation, data lake architecture, metadata standards, and self-serve analytics for the broader scientific team.
• Make strategic build-vs-buy decisions for tooling, compute, and third-party platforms.
• People Management
• Provide technical and professional management to a team of data scientists and engineers to enable end-to-end analysis pipeline
• Create an environment where high-autonomy individual contributors thrive: clear goals, minimal process overhead, rapid feedback loops.
• Foster a culture of rigorous, reproducible analysis and clear communication of results to non-computational audiences.
• Cross-Functional Partnership
• Translate wet-lab experimental goals into computational strategies and vice versa - surface data-driven insights that reshape assay design and instrument operation.
• Work with assay development to design experiments that generate high-quality training data and enable systematic evaluation of new chemistries (expanders, linkers, barcodes).
• Collaborate with the Head of Automation and hardware teams on instrument data integration and real-time analysis capabilities.
• Represent Data Science in management discussions, communicating progress, risks, and resource needs clearly.
• AI Strategy
• Champion the adoption of AI coding and analysis tools (Claude, Claude Code, etc.) across the data team and the broader organization.
• Evaluate how generative AI and LLMs can accelerate internal workflows: automated reporting, data exploration, code generation, and literature review.
• What You Need
• Required :
• MS or PhD in a quantitative field (Computer Science, Electrical Engineering, Computational Biology, Bioinformatics, Statistics, or related)
• 10+ years of post-academic experience in the omics space (genomics, proteomics, or related fields).
• 4+ years of experience managing technical teams (data scientists, ML engineers, or bioinformaticians), including hiring responsibility.
• Ability and willingness to operate as a player-coach: setting strategy while remaining hands-on with data, code, and models.
• Exceptional ability to identify, hire, and develop talent while establishing and enforcing standards of excellence in data science
• Capacity to develop both individual contributors and future managers within the team.
• Deep expertise in one of the following:
• Primary sequencing data analysis
• Machine learning applied to biological data
• Pipeline infrastructure and bioinformatics tooling
• Solid understanding of signal processing, classification, and machine learning techniques (transformers, CNNs, RNNs) and comfort applying them to sequencing or time-series data
• Practical familiarity with AWS, Nextflow, and modern bioinformatics tooling.
• Demonstrated ability to work at the bench-to-computation interface in collaborative research environments
• Ability to present complex technical results to non-technical stakeholders and to translate biological questions into computational approaches.

Requirements

• Direct experience with sequencing data, basecalling, read-level QC or nanopore signal-level analysis (strongly preferred).
• Experience building data infrastructure and analytics platforms in early-stage biotech.
• We're looking for

Benefits

Additional Information

About Glyphic: At Glyphic Biotechnologies, we plan to create the protein revolution for which scientists and researchers have been waiting. We are developing a massively parallel, single-molecule proteome sequencing platform that will transform life science discovery and usher in a new era of insights into human biology and disease. To date, we have raised >$80M from venture partners and non-dilutive grant funding to achieve our vision of next generation proteome sequencing. What we are looking for in you We are looking for a Director-level technical leader to build and lead Glyphic's Data Science function. This is a "player-coach" role. You must be technically deep enough to guide signal-processing and ML strategy for a novel nanopore-based protein sequencing platform, while also building the team culture, processes, and infrastructure needed to later scale from a larger data organization. You will report to the VP of R&D and work closely with team leads in assay development, chemistry, and automation. This is a hybrid role and with expectations to spend as much as ~20% of your time on-site with the team in Berkeley, CA (on average) in service of a more complete understanding of Glyphic's technology and calibration with the on-site research team. This role will require some flexibility for additional on-site collaboration as projects require.

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