Jobs at RA Capital Management

Build and operate production-grade healthcare data pipelines, models, and AI-enabled workflows. Develop Python and SQL solutions for data validation, reconciliation, and standardization; connect large language models with enterprise data, APIs, and internal tools; create governed LLM-to-SQL and LLM-to-GraphQL access frameworks; and implement agentic workflows, monitoring, observability, validation, and governance. Collaborate with engineering teams, vendors, and stakeholders to deliver reliable, compliant data and AI platforms.

Supports investor onboarding, documentation, reporting, subscriptions, redemptions, AML/KYC processes, transfer requests, tax reporting, cash clearance, and capital activity reconciliation. Coordinates with fund administrators, legal, accounting, finance, and investor relations teams; manages investor inquiries and due diligence requests; verifies quantitative reports; maintains process documentation and client service workflows; and supports marketing and due diligence materials.

Design and deploy AI systems that convert unstructured healthcare, scientific, and financial information into decision-relevant insights. Own applied AI projects from problem definition through deployment, evaluation, and improvement, using NLP, RAG, knowledge graphs, embeddings, entity extraction, and agentic systems. Develop evaluation frameworks, ensure data quality and reproducibility, and collaborate with investment professionals and senior stakeholders to support investment research and decision-making.

Conduct quantitative and qualitative primary market research across pharmaceutical therapeutic areas, focusing on value and access, pricing, and payer dynamics. Design surveys and study materials, manage research vendors, oversee fieldwork and data quality, analyze findings, and synthesize actionable insights for investment decisions. The role also requires applying and customizing AI tools to improve research workflows, analysis, and efficiency.

The AI Engineer will develop AI/ML solutions for investment analysis, design applications, optimize models, and work with large datasets in healthcare and finance contexts.

The Data Solutions Engineer will design and deliver data and analytics solutions, manage data pipelines, and support cloud platforms while collaborating with various teams to improve data accessibility and operational efficiency.