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Vice President, Product

Job in New York, New York County, New York, 10261, USA
Listing for: Formation Bio
Full Time position
Listed on 2026-05-03
Job specializations:
  • IT/Tech
    Data Analyst, AI Engineer (Applied/Software), Data Science Manager, Data Scientist
Salary/Wage Range or Industry Benchmark: 150000 - 200000 USD Yearly USD 150000.00 200000.00 YEAR
Job Description & How to Apply Below
Location: New York

About Formation Bio

Formation Bio is a tech and AI driven pharma company differentiated by radically more efficient drug development. Advancements in AI and drug discovery are creating more candidate drugs than the industry can progress because of the high cost and time of clinical trials. Recognizing that this development bottleneck may ultimately limit the number of new medicines that can reach patients, Formation Bio, founded in 2016 as Trial Spark Inc.,

has built technology platforms, processes, and capabilities to accelerate all aspects of drug development and clinical trials. Formation Bio partners, acquires, or in‑licenses drugs from pharma companies, research organizations, and biotechs to develop programs past clinical proof of concept and beyond, ultimately helping to bring new medicines to patients. The company is backed by investors across pharma and tech, including a16z, Sequoia, Sanofi, Thrive Capital, John Doe, Spark Capital, SV Angel Growth, and others.

About

The Position

Formation Bio is hiring Product Leads to own major problem domains across our drug development platform— for example, how we evaluate and acquire drug assets, how we design and run clinical trials, or how we build regulatory submissions. You will report to the CTO. This is a product leadership role, but not a traditional one. You won’t be writing specs for engineers to build.

You’ll own a business domain: set the strategy, define what to build, lead a cross‑functional team through delivery, and be measured on whether the work actually changes outcomes for the drug programs and business functions you serve. Your team will include engineers, data scientists, and product managers (ranging from senior ICs to managers). You will be embedded with our clinical, translational, regulatory, and business development leaders—to understand their problems deeply enough to identify where technology can make a material difference.

That means learning what makes a drug asset attractive, what drives a trial design decision, what the FDA cares about, and where the real time and cost sinks are. You should be able to drive value in a clinical review meeting in the same way you drive value in a sprint planning session. We are not building consumer software. We are building tools, models, and systems that make specific drug development decisions faster and better—prediction models that assess drug candidate viability, AI‑driven workflows that compress diligence timelines, and platforms that let non‑engineers build their own analytical tools.

You will own a slice of that work and be accountable for its impact.

Responsibilities
  • Own the product strategy for a defined problem domain (e.g., drug candidate evaluation, clinical trial execution, regulatory intelligence). Define what to build, what to deprioritize, and how to measure success.
  • Drive adoption of AI across your domain. We use LLMs, agentic workflows, and autonomous systems extensively. You should be pushing what's possible, not waiting for the technology teams to propose it.
  • Design systems that domain experts across the company can build on directly. Non‑engineers are already creating their own technology—your solutions should accelerate that, not bottleneck it.
  • Lead a cross‑functional team spanning engineering, data science, and product. Set the roadmap and make resourcing trade‑offs based on business impact.
  • Work directly with our core functional teams as a strategic tech partner. Translate their problems into technology solutions—not by taking feature requests, but by understanding the domain well enough to see opportunities they may not.
  • Guide the data science and engineering approach within your domain, including real‑world evidence analysis, prediction pipelines, clinical strategies, and dataset evaluation. You need enough technical judgment to know when an approach is sound and when to push back.
  • Maintain awareness of regulatory constraints. You don't need to be a regulatory expert, but you need to build products that work within GxP requirements and clinical data governance standards.
About You
  • 10+ years of experience in tech delivery with progressively broader scope, including…
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