Quantitative Research and Strategy, Healthcare AI Associate

Quantitative Research and Strategy, Healthcare AI Associate

Imagine if you had the skills, knowledge, and teammates to both understand the root of the world’s most pressing problems and build the technologies and companies best positioned to solve them. RA Capital has done exactly that for more than two decades, backing bold ideas in medicines to further human health and now expanding into Planetary Health to improve how efficiently we utilize the world’s precious resources.

RA Capital is among the leading providers of capital and services to the most promising innovators in the world. We invest flexibly—seed to IPO and beyond, anywhere in the world—with $10 B+ under management and a culture that prizes curiosity, rigor, and collaborative debate.

If you live for first‑principles problem‑solving with great colleagues, thrive on complexity, and want to do meaningful work that ripples across industries and ecosystems, you’ll feel at home at RA Capital. Here, questions are welcomed, ideas are tested, and victories are shared.

Are you ready to bring your creativity, discipline and collaborative spirit to help us invent the future? Join us and you’ll collaborate daily with investors, founders, physicians, biologists, engineers, economists, and reform advocates who think in systems and act with urgency.

The Quantitative Research & Strategy (QRS) team within RA Capital helps inform investment decisions and improve core processes with data‑driven analyses. The team focuses on three core areas: portfolio management, risk management, and data science. They leverage complex datasets to uncover insights related to trends, patterns, and key drivers within the healthcare and financial landscapes. The team operates on a wide variety of projects in a fast‑paced environment;

often collaborating across teams (Invest, Venture, Legal, Finance, Compliance, Tech Atlas, etc) and working directly with senior leadership & portfolio managers.

As an Associate within the QRS team, you will be working on diverse quantitative and qualitative analytical problems requiring you to:

• Design and build systems to transform unstructured data into usable, structured representations (e.g., knowledge graphs, embeddings, and linked datasets) that can be queried and analyzed by the investment team.
• Develop and deploy AI‑driven workflows (e.g., LLM pipelines, retrieval systems, entity extraction, relationship mapping) to surface relevant insights from large corpora of text and other unstructured sources.
• Collaborate with the investment team to integrate data‑driven insights into investment strategies.
• Combine insights from healthcare data, financial information, and data analytics into cohesive stories and actionable narratives for RA’s investing team.
• Develop dashboards and visualizations to communicate findings effectively.
• Ensure data quality and integrity by implementing best practices in data collection, processing, and storage.

We are looking for curious, intelligent, and driven individuals with a strong interest in the intersection of healthcare, financial markets and data science, capable of delivering results in a timely manner and at the highest levels of quality. All applicants must meet the following criteria to be considered:

• Must be authorized to work in the United States.
• Must have a Bachelor’s (or higher) in a STEM or finance/economics degree.
• Must have 2+ years of experience working with unstructured data in AI systems.
• Experience designing and implementing systems for unstructured data, such as:
  • Knowledge graphs or graph‑based data models
  • Vector databases / embedding‑based retrieval systems
  • Entity extraction, linking, and relationship mapping
• Familiarity with modern AI/LLM tooling (e.g., retrieval‑augmented generation, prompt pipelines, evaluation frameworks) and an understanding of their limitations in high‑stakes settings.
• Experience working with Spark (pyspark), SQL, and Python.
• Must be curious, flexible, and able to adapt quickly to changing projects and priorities.
• Must be based in Massachusetts (consideration will be given to applicants who are willing and able to relocate to MA).
• Must be able to work on…