Scientist, Computational Biology

Position Overview

The position is for a Scientist, Computational Biology to join MyOme's early-stage research team. MyOme combines clinical-grade whole genome sequencing, advanced AI methods for genome interpretation, and seamless digital tools for ordering and accessing results.

What You'll Do

• Biobank Data Mining: Ingest, process, and perform quality control on large-scale public human datasets, with an emphasis on the UK Biobank and the All of Us Research Program.
• Multi-Omics Analysis: Analyze complex human molecular profiling data, drawing from modalities such as plasma proteomics (e.g., Olink, SomaScan), metabolomics, genome-wide DNA methylation, and transcriptomics.
• Risk Prediction & Observational Epidemiology: Apply biostatistical, observational, and machine learning methods (e.g., survival analysis, Cox models, longitudinal trajectory analysis) to evaluate phenotype associations and early disease risk.
• Feasibility & Proof-of-Concept: Design and execute fast computational experiments to determine whether specific multi-omic panels add incremental predictive value over standard clinical risk factors or polygenic risk scores.
• Cross-Functional Collaboration: Partner closely with computational scientists, assay scientists, clinical and regulatory experts, and product development stakeholders to communicate analytical findings and help prioritize targets/markers for experimental validation.

What You'll Need

• Education & Experience: Ph.D. in Computational Biology, Bioinformatics, Biostatistics, Epidemiology, Human Genetics, or a related quantitative field with 0–4 years of experience (or Master’s degree with 3–6+ years of relevant experience).
• Biobank Expertise: Proven hands-on experience querying and analyzing multi-modal data in major human cohorts, specifically UK Biobank and/or All of Us.
• Omic Proficiency: Demonstrated experience analyzing at least two of the following human data types: Plasma proteomics, Metabolomics, Genome-wide DNA methylation (array or sequencing), Bulk/single-cell transcriptomics.
• Epidemiological & Statistical Rigor: Strong background in observational study design, association testing, confounding control, and time-to-event modeling on clinical/EHR phenotypes.
• Computational Toolkit: High proficiency in Python and/or R, version control (Git), and working in cloud-based biobank environments (e.g., DNAnexus, Terra, AWS, or GCP).
• Statistical Methods & Machine Learning: Well-versed in statistical approaches applicable to biomarker discovery (e.g., high-dimensional feature selection, hypothesis testing, regularization) and experienced with standard machine learning workflows (e.g., random forests, gradient boosting, penalized regression); hands-on experience with deep learning methodologies is preferred.

Preferred / Bonus Qualifications

• Experience constructing integrated multi-omic risk scores or combining omics with Polygenic Risk Scores (PRS).
• Familiarity with causal inference methods (e.g., Mendelian Randomization).
• Experience working in an agile, early-stage biotech startup environment.

Location, Compensation, and Benefits

• Location: Hybrid role, 2 to 3 days onsite at our Menlo Park, CA office.
• Compensation: Annual salary range of $130,000 - $150,000, commensurate with experience. This role is also eligible for equity.
• San Francisco Bay Area pay range: $130,000 USD - $150,000 USD.
• Benefits: Comprehensive healthcare coverage (Health, Dental, and Vision), 401K, Unlimted PTO.

Diversity, Inclusion, and Equal Opportunity

MyOme values diversity in all forms. We believe that diverse perspectives drive better science and better patient outcomes. We are an Equal Opportunity Employer committed to creating an inclusive workplace that empowers every individual.

Why Work at MyOme?

• Make an impact at the intersection of healthcare and technology, changing the way people engage with their health at the genetic level.
• Taking initiative and being empowered to lead.
• Humility, transparency, and collaborative problem-solving.
• Fast-moving, dynamic environments with smart, driven teammates.
• Competitive compensation, meaningful equity, and excellent benefits.

Learn More

Learn More