Data Scientist (Open Level)

Formation Bio•Boston, NY

17h•Hybrid

About The Position

As a Data Scientist at Formation Bio, you will lead initiatives that support drug development, including developing models for patient selection and creating AI-powered solutions for clinical trial optimization. You will work at the intersection of computational biology, machine learning, and drug development, collaborating with cross-functional teams to turn complex biological data into actionable insights. The role offers the opportunity to apply AI technologies to pharmaceutical development and contribute to bringing treatments to patients faster and more efficiently. Formation Bio is a technology- and AI-driven pharmaceutical company focused on making drug development and clinical trials more efficient. Founded in 2016 as TrialSpark Inc., the company partners with, acquires, or in-licenses drug programs and develops them past clinical proof of concept and beyond. The role uses a hybrid model requiring three days per week in the office. Formation Bio is prioritizing candidates in the New York City and Boston metro areas; applicants from the Research Triangle in North Carolina and the San Francisco Bay Area may also be considered. Applicants must reside in these locations or be willing to relocate. Total compensation ranges from $161,500 to $267,000, with equity, comprehensive benefits, and generous perks. Individual compensation depends on role scope, geographic location, skills, and experience.

Requirements

PhD in computational sciences or life sciences.
3–5+ years of post-academic experience in life sciences, such as biotech, pharma, or consulting.
Strong programming skills, particularly in Python.
Extensive experience in multimodal bioinformatics analysis.

Nice To Haves

Expertise in cloud computing environments, including proficiency with tabular and/or graph databases.
Strong background in machine learning and deep learning, particularly in biological applications.
Experience with large language models (LLMs).
Ability to collaborate effectively with engineering teams on production systems.
Strong communication skills and demonstrated ability to present complex technical findings to senior stakeholders.

Responsibilities

Lead and execute complex data science projects that directly advance the drug development portfolio.
Develop and implement models for therapeutic hypothesis evaluation, including patient stratification and biomarker identification.
Design and create AI models to modernize clinical trial evaluations, including surrogate endpoints.
Aid in developing and training AI agents to automate and optimize biomedical workflows.
Collaborate with clinical, technical, and research teams.
Present complex analytical findings to senior stakeholders, including executive leadership.