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Bioinformatics Ontology Jobs (NOW HIRING)

NewsBreak

Local POI Knowledge Graph

Mountain View, CA

$142K/yr

POI / places data systems, schema, and ontology for local businesses and listings. * Own entity resolution and entity linking across multiple, conflicting data sources. * Build merchant / listing ...

NewsBreak

Local POI Knowledge Graph

Mountain View, CA · On-site

$142K - $342K/yr

POI / places data systems, schema, and ontology for local businesses and listings. * Own entity resolution and entity linking across multiple, conflicting data sources. * Build merchant / listing ...

Jj

Senior Scientist Omics - IMM

Spring House, PA · On-site

$87K - $119K/yr

Construct an analytic framework by integrating perturbation, ontology and cellular phenotyping with ... D. in a quantitative Biology field - Bioinformatics, Computational Biology, Systems Biology ...

Jj

Principal Data Scientist - Oncology

Titusville, NJ · On-site

You will be a hands-on technical contributor with depth in semantic technologies, ontology, and ... D. or Master's degree in bioengineering, computer science, IT, bioinformatics, physics, mathematics ...

Jj

Principal Data Scientist - Oncology

San Diego, CA · On-site

You will be a hands-on technical contributor with depth in semantic technologies, ontology, and ... D. or Master's degree in bioengineering, computer science, IT, bioinformatics, physics, mathematics ...

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Bioinformatics Ontology information

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$59.5K

$94.5K

$149.5K

How much do bioinformatics ontology jobs pay per year?

As of Jun 29, 2026, the average yearly pay for bioinformatics ontology in the United States is $94,474.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,500.00 and $129,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Bioinformatics Ontologist, and why are they important?

To thrive as a Bioinformatics Ontologist, you need a strong background in biology, bioinformatics, and knowledge representation, often supported by a degree in bioinformatics, computer science, or a related field. Familiarity with ontology development tools (such as Protégé), semantic web technologies (like OWL and RDF), and databases is essential, along with experience in standards such as Gene Ontology. Attention to detail, analytical thinking, and effective communication are vital soft skills for building and maintaining complex ontologies and collaborating with multidisciplinary teams. These competencies ensure the creation of reliable, interoperable ontological resources that advance data integration and discovery in the life sciences.

How does a Bioinformatics Ontology professional typically collaborate with domain experts and software engineers on a project?

Bioinformatics Ontology professionals often serve as a bridge between subject matter experts, such as biologists, and technical teams like software engineers. They work closely with domain experts to accurately capture and represent biological concepts, ensuring that the ontology reflects current scientific understanding. Simultaneously, they collaborate with software engineers to integrate ontologies into databases and applications, facilitating effective data retrieval and interoperability. Strong communication and project management skills are essential in this role, as collaboration is continuous throughout a project's lifecycle.

What is bioinformatics ontology?

Bioinformatics ontology is a structured framework that organizes and defines the relationships between biological and biomedical concepts, such as genes, proteins, diseases, and experimental methods. These ontologies help standardize terminology and enable consistent data annotation, integration, and sharing across different databases and research studies. They play a crucial role in facilitating computational analysis and interoperability in bioinformatics by providing a common language for researchers. Examples include the Gene Ontology (GO) and Disease Ontology, which are widely used in genomics and medical research.

What is the difference between Bioinformatics Ontology vs Bioinformatics Analyst?

AspectBioinformatics OntologyBioinformatics Analyst
Required CredentialsTypically requires a background in bioinformatics, computer science, or biology; familiarity with ontologies and data modelingBachelor's or master's in bioinformatics, biology, or related fields; programming skills beneficial
Work EnvironmentResearch labs, academic institutions, or bioinformatics tool development teamsHealthcare, research institutions, biotech companies, analyzing biological data
Employer & Industry UsageUsed in data annotation, knowledge representation, and database integration within bioinformaticsData analysis, interpretation, and reporting in biological research and clinical settings

Bioinformatics Ontology focuses on developing structured frameworks for biological data, while Bioinformatics Analysts interpret and analyze this data to support research and decision-making. Both roles are essential but serve different functions within the bioinformatics field.

More about Bioinformatics Ontology jobs
What cities are hiring for Bioinformatics Ontology jobs? Cities with the most Bioinformatics Ontology job openings:
What states have the most Bioinformatics Ontology jobs? States with the most job openings for Bioinformatics Ontology jobs include:
What job categories do people searching Bioinformatics Ontology jobs look for? The top searched job categories for Bioinformatics Ontology jobs are:
Bioinformatics Ontology jobs near you
Infographic showing various Bioinformatics Ontology job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $94,474 per year, or $45.4 per hour.

Data Scientist, Knowledge Graphs

Mithrl

San Francisco, CA • On-site

$150K - $200K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 11 hours ago

Key responsibilities

  • Ingest, harmonize, and version high value public biological datasets and peer reviewed knowledgebases into a unified knowledge graph.

  • Build automated pipelines to curate, expand, and maintain relationships, schemas, and metadata within the knowledge graph.

  • Develop tools and frameworks that allow users to explore, interact with, and build custom knowledge graphs based on their analyses.

Job description

ABOUT MITHRL
We imagine a world where new medicines reach patients in months, not years, and where scientific breakthroughs happen at the speed of thought.
Mithrl is building the world's first commercially available AI Co-Scientist. It is a discovery engine that transforms messy biological data into insights in minutes. Scientists ask questions in natural language, and Mithrl responds with real analysis, novel targets, hypotheses, and patent-ready reports.
Our traction speaks for itself:
  • 12X year-over-year revenue growth
  • Trusted by leading biotechs and big pharma across three continents
  • Driving real breakthroughs from target discovery to patient outcomes.

ABOUT THE ROLE
We are hiring a Data Scientist, Knowledge Graphs to build and scale the biological knowledge layer that powers the Mithrl AI Co-Scientist. This role focuses on ingesting and harmonizing the world's most important biological data sources and curating the relationships that allow our system to reason across pathways, targets, diseases, compounds, and multimodal datasets.
You will ingest data from public consortia and well maintained peer reviewed sources and unify them into a coherent, versioned knowledge graph. You will identify new node types, define relationship schemas, harmonize variable IDs, and ensure metadata remains consistent across all integrated sources. You will also build automated curation pipelines that expand and refine the knowledge graph using both data driven methods and domain logic.
Beyond ingestion and curation, you will create the tools and frameworks that allow users to interact with the knowledge graph and even build their own custom graphs based on the results they generate inside Mithrl. Your work will form the foundation for pathway reasoning, target scoring, evidence aggregation, and multimodal interpretation inside the AI Co-Scientist.
WHAT YOU WILL DO
  • Ingest, harmonize, and version high value public biological datasets such as CellxGene, Gemma, ARCHS4, ENCODE, GTEx, TCGA, etc.
  • Ingest well maintained peer reviewed knowledgebases including OpenTargets, HPA, and similar resources
  • Build automated pipelines to curate and expand relationships inside the knowledge graph
  • Define and evolve schemas for node types, relationships, metadata rules, and ontology alignment
  • Harmonize variable IDs and metadata fields across all imported sources to create a unified knowledge layer
  • Build and maintain versioning, change tracking, and provenance systems for all data and relationships
  • Develop the framework that allows users to build custom knowledge graphs from the analyses they run inside Mithrl
  • Build features that allow users to explore, query, and interact with their graphs
  • Work closely with ML engineers, bioinformatics teams, and discovery application teams to ensure the knowledge graph supports downstream reasoning and analysis
  • Validate the correctness, completeness, and integrity of the knowledge graph across releases

WHAT YOU BRING
Required Qualifications
  • Strong experience in data science, bioinformatics, computational biology, or a related field
  • Experience working with biological knowledgebases, public datasets, or ontology driven systems
  • Familiarity with graph data structures, relationship modeling, and knowledge graph concepts
  • Experience harmonizing heterogeneous biological datasets and mapping variable IDs across sources
  • Proficiency in Python and scientific computing libraries
  • Ability to build ingestion pipelines for structured or semi structured biological data
  • Strong understanding of metadata standards, biological ontologies, and domain logic
  • Ability to translate complex biological information into structured, machine readable representations
  • Excellent communication skills and comfort collaborating across engineering and scientific teams

Nice to Have
  • Experience with graph databases or graph query languages
  • Experience with KG curation, link prediction, relationship extraction, or graph based ML
  • Familiarity with multi modal data integration
  • Previous work on biological or chemical knowledge graphs
  • Experience with public consortia such as ENCODE, GTEx, TCGA, or ChEMBL, etc.
  • Prior experience in a tech bio startup or scientific software environment

WHAT YOU WILL LOVE AT MITHRL
  • You will build the core knowledge layer that the AI Co-Scientist uses to reason about biology
  • Team: Join a tight-knit, talent-dense team of engineers, scientists, and builders
  • Culture: We value consistency, clarity, and hard work. We solve hard problems through focused daily execution
  • Speed: We ship fast (2x/week) and improve continuously based on real user feedback
  • Location: Beautiful SF office with a high-energy, in-person culture
  • Benefits: Comprehensive PPO health coverage through Anthem (medical, dental, and vision) + 401(k) with top-tier plans

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Apply