About Oath

Oath is a leading microbial sciences company that utilizes natural soil biology to offer innovative solutions to some of the most critical challenges facing our planet - the climate crisis and the shift to sustainable agriculture. We imagine a world where these crises are not just alleviated, but reversed, replenishing Earth's microbiomes.

Our solution has moved beyond the lab and into real-world deployment, focused on improving farmer livelihoods with teams in Rwanda, Europe, the United States, and expanding. When you join Oath, you become part of a collaborative network that prioritizes high quality scientific work. You will be working alongside trained scientists, talented commercial teams, and a broad network of partners—an ecosystem designed to help you do your best work and grow your capabilities.

Position Summary

We're looking for a Bioinformatics Analyst to join our Biome R&D team and help translate microbiome and genomics data into decisions that move Oath's science forward. You'll independently develop manuscript-quality reports, figures, and executive summaries that interpret how our internal microbe collection displays plant-beneficial traits in target soils, working closely with our bioinformatics team and a broad network of scientific collaborators. This is a high-impact role for a curious, detail-oriented problem-solver who wants their comparative genomics and data analysis expertise to directly shape real-world agricultural solutions.

Key Responsibilities

• Independently produce high-quality reports and communicate key outcomes to both technical and non-technical audiences.
• Translate complex tabular and plot-based outputs from high-throughput analysis pipelines into novel hypotheses and action items that drive project success.
• Perform statistical analyses, including compositional data analysis (differential abundance, transformations, associations), parametric/non-parametric two-sample tests (e.g., t-test, Mann-Whitney U), categorical association tests (e.g., chi-squared, Fisher's exact test), permutation tests, and association analysis across continuous, compositional, and binary data.
• Programmatically generate visualizations - including scatter, bar, box, and heatmap plots, and phylogenetic/hierarchical clustering dendrograms - applying best practices for choosing the right visualization for the data.
• Apply unsupervised learning methods (e.g., hierarchical clustering, dimensionality reduction) to interpret pairwise similarities and distances, and work with N-dimensional data structures (indexing, masking, broadcasting, vectorized operations).
• Install, run, and troubleshoot prebuilt bioinformatics workflow frameworks, including Conda, Nextflow, QIIME2, and various CLI tools.
• Collaborate with colleagues across disciplines to import and export data into Oath's data registries.
• Build and evaluate pangenomes, compare proteins across genomes, and perform protein annotation (BLAST-based/HMM-based) to support comparative genomics work.

Qualifications

Required:

• A minimum of a Master's degree with a background in Computational Biology or a related field, with specific expertise in genome sequencing and metagenomics analysis.
• Proficiency in Python, R, and Bash, with hands-on experience using Conda and the Nextflow framework.
• Experience with quality control and evaluating batch effects in omics analyses, and LIMS/data management proficiency (e.g., Benchling and/or Odoo).
• Strong scientific communicator, able to deliver the results of a complex process to audiences with a broad range of specialties and collaborate effectively across disciplines.
• Strong problem-solving skills and attention to detail, with the ability to learn, apply, and troubleshoot new methodologies.

Preferred:

• Academic or industry experience working with plant-microbe interactions and indicators of soil health.
• Experience developing high-quality reports for international filings with regulatory authorities.
• Modern proficiency with best practices in published bioinformatics toolsets and processing libraries.
• Experience developing and evaluating machine learning models (e.g., cross-validation, classification metrics, class imbalance).
• Highly responsive, collaborative, proactive, and adaptable to changing project needs.
• Familiarity with GoogleSuite, Excel, Slack and similar tools is a plus.

Job Type: Full-time, non-exempt position in the United States. At this time, Oath, Inc. is not able to provide visa sponsorship or work authorization support.

Location: Remote or hybrid; preferentially based in US Central or Pacific time zones