Senior Data Analyst - AI Evaluation (Life Sciences)

Job highlights

• Experience evaluating AI or algorithmic outputs using scientific data
• Experience applying scientific expertise in structured data or content environments,such as databases,taxonomies,knowledge graphs,or similar systems

Job Summary

Senior Data Analyst - AI Evaluation (Life Sciences).

Automate and conduct LLM-as-jury evaluations to improve AI-powered life sciences solutions through scientific expertise and rigorous analysis.

About the Team

We are a growing team working on the evaluation of AI systems in development and on cross-domain harmonization. Our mission is to enable better, more trustworthy AI-driven products by combining scientific expertise with rigorous evaluation and AI-ready data. We generate actionable evidence that accelerates product improvement, and we unlock greater value from curated scientific knowledge by making it interoperable, interpretable, and reliably usable by AI across domains.

About the Role

The Senior Data Analyst - AI Evaluation will support the evaluation of AI-powered solutions that use life sciences, chemistry, and regulatory data. Working with scientific domain experts, product, data science, and engineering teams, you will contribute to evaluation strategies and rubrics, evaluation scenarios, and acceptance criteria that reflect customer needs and product goals.

A key focus of this role is adapting and validating automated evaluation approaches. Using an LLM as jury framework, you will tailor evaluation criteria and methods to specific products, use cases, and metrics. You will assess the reliability of automated judgments, identify gaps or inconsistencies, and refine the approach in collaboration with relevant experts.

Through structured analysis, domain-informed judgment, and iterative validation you will contribute to more robust evidence of quality, faster feedback cycles for product development, and stronger alignment with real-world scientific and customer requirements.

Responsibilities

• Applying scientific expertise to contribute to customer-focused success criteria, evaluation rubrics, and acceptance criteria for AI solutions.

• Contributing to the definition of evaluation scope, metrics, and scenarios using domain knowledge across drug discovery, drug development, and regulatory approval.

• Building and curating scientific test sets and benchmarks that reflect real-world use of life sciences and regulatory data.

• Adapting LLM-as-jury evaluation approaches to specific products, use cases, and metrics, and validating and refining their performance in collaboration with scientific domain experts.

• Conducting manual and automated evaluations of AI outputs, investigating discrepancies and failure modes, and providing evidence-based feedback on evaluation quality.

• Working closely with product, data science, and engineering teams to understand how AI systems access, interpret, and use scientific data.

• Documenting evaluation findings, limitations, and recommendations clearly for cross-functional teams to support product improvements and release decisions.

  Requirements

• Strong academic background in life sciences, such as bioinformatics, cheminformatics, biochemistry, pharmacology, or a related field.

• Experience evaluating AI or algorithmic outputs using scientific data.

• Experience applying scientific expertise in structured data or content environments, such as databases, taxonomies, knowledge graphs, or similar systems.

• Familiarity with how AI products access and use data, including a general understanding of data flows, APIs, and version-controlled workflows such as GitHub.

• Collaborative mindset and clear communication skills.

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