Bioinformatics Scientist – Epigenomics and Computational Methods

Zymo Research Corporation•Irvine, CA

7d•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, discover and evaluate candidate methylation biomarkers, develop statistical models, and build reproducible analysis pipelines in collaboration with experimental scientists. The scientist will guide computational strategy, define analytical performance criteria, and support targeted assay development, independent validation, and transfer into scalable research products. The position owns the computational roadmap for assigned research and assay development projects, coordinating priorities and dependencies with experimental scientists and supporting bioinformatics teams. It includes curation of public and internal epigenomic datasets, discovery and prioritization of molecular markers and differentially methylated regions, and development and benchmarking of statistical models for molecular profiling and epigenetic biomarker analysis. The scientist builds and validates reproducible pipelines for methylation sequencing and reference array datasets, co-designs targeted methylation panels, and benchmarks analytical methods using reference standards, simulations, and independent sample sets. The role also defines quantitative reporting metrics and quality thresholds, implements automated quality checks and traceable software releases, provides technical guidance and code review, maintains documentation, contributes to publications and invention disclosures, and supports product and customer-facing technical discussions as needed.

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 closely 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/posters, validated analytical methods, or deployed analysis tools such as GitHub.
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/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 (Nanopore/PacBio), low-input assays, uncertainty estimation, workflow engines, or transfer of analytical methods into supported research products.

Responsibilities

Own the computational roadmap 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 support 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, common sequence variants, repetitive regions, assay compatibility, and stability.
Develop and benchmark statistical models for molecular profiling and epigenetic biomarker analysis.
Build reproducible pipelines for methylation sequencing and relevant reference array datasets, including 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 and assess primers, probes, and hybridization capture baits in silico.
Benchmark analytical methods using reference standards, simulations, and independent sample sets; assess bias, error, agreement, reproducibility, and robustness.
Assess robustness to sequencing depth, missing data, DNA input, dataset selection, platform differences, batch effects, and biological variation.
Use validated harmonization approaches 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 to scientific and product teams.
Implement automated quality checks, failure flags, versioned reports, and traceable software releases.
Use code review, tests, workflow automation, and documented environments to support reproducibility and technical transfer.
Provide technical guidance and code review for collaborating scientists and junior bioinformatics staff.
Maintain clear analysis documentation, contribute to publications and invention disclosures, and support relevant product and customer-facing technical discussions.