Bioinformatics Scientist – Epigenomics and Computational Methods

Zymo Research Corporation•Irvine, CA

15h•$85,000 - $115,000•Onsite

About The Position

Zymo Research is seeking a Bioinformatics Scientist to join its Epigenetics Technology team and lead computational development for epigenomics and molecular assay research. The role combines epigenomics, statistical modeling, and software development. The scientist will curate datasets, identify and evaluate candidate methylation biomarkers, develop statistical models, and build reproducible analysis pipelines in close collaboration with experimental scientists. They will guide computational strategy, define analytical performance criteria, and support targeted assay development, independent validation, and transfer into scalable research products. The role includes ownership of computational roadmaps for assigned research and assay development projects; curation and documentation of public and internal epigenomic datasets; discovery and evaluation of molecular markers and differentially methylated regions; and development and benchmarking of statistical models. The scientist will build, validate, and maintain reproducible methylation analysis pipelines, co-design targeted panels, assess performance and robustness, define quantitative reporting metrics, and support traceable software releases and technical transfer. The position also provides technical guidance and code review to collaborating scientists and junior bioinformatics staff. It contributes to analysis documentation, publications, invention disclosures, and product- and customer-facing technical discussions as needed. Zymo Research describes itself as a provider of research tools and products across DNA, RNA, epigenetics, microbiomics, protein, and yeast-based research. The position is onsite at Zymo Research headquarters in Irvine, California.

Requirements

Ph.D. in bioinformatics, computational biology, computer science, genomics, or a related discipline.
Demonstrated independent ownership of substantial computational research or product development projects.
Strong experience analyzing DNA (hydroxy)methylation or epigenomic data, including sequencing-based quantification, quality control, and biological interpretation.
Experience with statistical modeling, biomarker discovery, or related quantitative methods, including rigorous study design, feature selection, and independent model validation.
Proficiency in Python and R, Linux or Unix, statistical analysis, and scientific visualization.
Experience building maintainable analysis code with version control, automated tests, and documented workflows.
Experience processing Illumina sequencing data, managing large genomic datasets, and developing scalable workflows using high-performance or cloud computing environments.
Experience with epigenomic biomarker discovery, dataset curation, method benchmarking, or statistical model optimization.
Strong communication skills and evidence of original scientific contributions through publications or posters, validated analytical methods, or deployed analysis tools.
Ability to explain uncertainty and analytical tradeoffs to multidisciplinary collaborators.

Nice To Haves

Experience with targeted methylation sequencing, hybridization capture panel design, multiplex primer or probe design, or analysis of methylation-sensitive qPCR or digital PCR data.
Experience analyzing DNA variants or SNPs using NGS data and appropriate quality control and validation methods.
Experience comparing molecular assay results with independent measurements and assessing analytical agreement, bias, and reproducibility.
Experience with cross-platform methylation analysis using Nanopore or PacBio, low-input assays, uncertainty estimation, workflow engines, or transfer of analytical methods into supported research products.

Responsibilities

Own computational roadmaps for assigned research and assay development projects, including deliverables, milestones, acceptance criteria, data needs, and technical risks; coordinate priorities and dependencies with experimental scientists and bioinformatics teams.
Curate public and internal epigenomic datasets, documenting provenance, quality, metadata, assay platform, genome build, usage permissions, and dataset inclusion and quality criteria.
Discover and prioritize candidate molecular markers and differentially methylated regions, evaluating specificity, biological variability, sequence variants, repetitive regions, assay compatibility, and stability across sample and biological conditions.
Develop and benchmark statistical models for molecular profiling and epigenetic biomarker analysis, evaluating feature selection, model assumptions, uncertainty, and performance.
Build reproducible pipelines for methylation sequencing and relevant reference array datasets, covering quality control, alignment, methylation quantification, filtering, annotation, and reporting.
Evaluate conversion efficiency, mapping ambiguity, duplicates, coverage, and batch effects using assay-appropriate controls.
Co-design targeted methylation panels with the assay team; assess primers, probes, and hybridization capture baits in silico and use empirical enrichment and coverage data to refine panel designs.
Benchmark analytical methods using reference standards, simulations, and independent sample sets; assess bias, error, agreement, reproducibility, and robustness while separating development, marker selection, and validation by biological source.
Assess robustness to sequencing depth, missing data, DNA input, dataset selection, platform differences, batch effects, and biological variation; use validated harmonization methods and prevent information leakage across development and validation datasets.
Define quantitative reporting metrics, calibration approaches, quality thresholds, and validated reporting ranges; document uncertainty, investigate unexpected results, and communicate analytical limitations.
Implement automated quality checks, failure flags, versioned reports, and traceable software releases using code review, tests, workflow automation, and documented environments.
Provide technical guidance and code review for collaborating scientists and junior bioinformatics staff.
Maintain clear analysis documentation; contribute to publications and invention disclosures; support product- and customer-facing technical discussions as needed.
Contribute to other projects requiring relevant scientific and technical expertise.