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.
Top Skills
What We Do
Scientific labs waste weeks learning & coding pipelines that do not carry over to the next experiment. Using just natural language, Mithrl builds them custom workflows for NGS data on-demand, in minutes -- not weeks. This allows them to focus all their time on running higher quality experiments.
