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Data Scientist - Knowledge Graphs at mithrl | San Francisco

mithrlSan Francisco
On-site Full-time

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Experience Level

Entry Level

Qualifications

We are looking for candidates with a strong foundation in data science, particularly with experience in knowledge graphs and biological data. Proficiency in programming languages such as Python or R, along with familiarity with data processing frameworks, is essential. A solid understanding of biological concepts and datasets will be beneficial. Candidates should possess excellent problem-solving skills and the ability to work collaboratively in a fast-paced environment.

About the job

ABOUT MITHRL

At Mithrl, we envision a future where innovative medicines are delivered to patients in mere months, not years, and where scientific discoveries unfold at the speed of thought.

Mithrl is pioneering the world’s first commercially available AI Co-Scientist, a groundbreaking discovery engine that converts complex biological data into actionable insights within minutes. Scientists interact using natural language, and Mithrl provides real analysis, innovative targets, hypotheses, and patent-ready reports.

Our impressive track record includes:

  • 12X year-over-year revenue growth

  • Endorsed by leading biotech firms and major pharmaceutical companies across three continents

  • Facilitating significant breakthroughs from target discovery to patient outcomes.

ABOUT THE ROLE

We are seeking a Data Scientist specializing in Knowledge Graphs to develop and enhance the biological knowledge layer that supports the Mithrl AI Co-Scientist. Your primary focus will be to aggregate and harmonize the most critical biological data sources globally, curating the relationships that enable our system to reason across various pathways, targets, diseases, compounds, and multimodal datasets.

You will be responsible for gathering data from public consortia and well-maintained peer-reviewed sources to create a coherent, versioned knowledge graph. This includes identifying new node types, defining relationship schemas, harmonizing variable IDs, and ensuring metadata consistency across all integrated sources. Additionally, you will build automated curation pipelines that enrich and refine the knowledge graph through both data-driven approaches and domain knowledge.

Beyond data ingestion and curation, you will develop tools and frameworks that empower users to interact with the knowledge graph and create their custom graphs based on the insights generated within Mithrl. Your contributions will lay the groundwork for pathway reasoning, target scoring, evidence aggregation, and multimodal interpretation within the AI Co-Scientist.

WHAT YOU WILL DO

  • Aggregate, harmonize, and version high-value public biological datasets such as CellxGene, Gemma, ARCHS4, ENCODE, GTEx, TCGA, etc.

  • Ingest well-maintained peer-reviewed knowledge bases such as OpenTargets, HPA, and similar resources.

  • Create automated pipelines to curate and broaden relationships within the knowledge graph.

  • Define and evolve relationship schemas, ensuring accuracy and consistency throughout.

About mithrl

Mithrl is at the forefront of utilizing artificial intelligence in the life sciences, enabling faster and more effective drug discovery processes. With a commitment to innovation, we are transforming how scientists interact with data, ensuring that crucial medical advancements are accessible sooner.

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