Data Scientist / Senior Data Scientist

Quantile Health AI-Powered Insights for Life Science

Quantile Health is a New York-based, seed-stage AI startup on a mission to expand patient access to life-changing medicines while cutting commercial costs for drug innovators

Role: AI & Data Science LLMs & Healthcare Insights

We're looking for a data-driven problem solver to leverage large language models (LLMs) and transform unstructured data into data ontologies and actionable insights that drive drug launches and access strategies. You'll work at the intersection of AI, data science, and healthcare, helping biotech and pharma companies navigate patient access barriers and optimize commercial decisions.

What You’ll Do

• Design and implement agentic LLM workflows from the ground up to drive impactful business outcome

• Build and optimize data pipelines for processing structured & unstructured data.

• Select, evaluate, and fine-tune LLMs for key business applications

• Ensure data integrity, accuracy, and usability for analytics & decision-making

• Collaborate with engineering teams to shape data infrastructure & model development

What We’re Looking For

• A strong conceptual thinker who thrives on turning complex, ambiguous business challenges into clear data problems - especially when there’s no obvious solution.

• Passionate about LLMs and their real-world applications, with a pragmatic, impact-driven mindset - focused on solving the right problems and delivering meaningful results over perfect models.

• PhD in a quantitative field (CS, Data Science, Computational Biology, Stats, etc.) OR Bachelor/Master + 2+ years of experience in finance, biotech, or tech startup.

• Strong Python skills (SQL is a plus).

• Experience in prompt engineering, statistical modeling, and advanced analytics.

• Hands-on experience with large datasets & unstructured data transformation.

Compensation & Benefits

Cash compensation range: $155,000 - $225,000
Equity grants in Quantile Health
Unlimited PTO
Employee benefits package

Location: Hudson Yards, NYC (on-site 2 days a week)