Senior Product Manager

Verantos

4h•Remote

About The Position

Verantos is the global leader in high-validity real-world evidence (RWE) for life sciences. Our product strategy is built on three modular, connected pieces — the Curation Platform (raw data to structured, validated variables), Pragmatic Registry data sets (high validity, enriched datasets), and the Evidence Platform (standardized data to evidence). As Senior Product Manager, you will own the product that turns the richest, most difficult clinical data into trusted, structured evidence. You will support teams to build reference standards, train and validate AI models, and measure accuracy with full transparency aligned with FDA guidance. You will set the vision and roadmap as a hands-on, AI-native product manager.

Requirements

Bachelor's degree in a technical, scientific, or medical field from a reputed institution
Significant product management experience, including senior-level ownership of one or more AI-powered products or components, with full B2B product lifecycle experience and products currently in commercial use
Demonstrated fluency working in an AI-native, prototype-first way: hands-on use of LLMs (e.g., Claude, ChatGPT, Gemini) and building tools (e.g., v0, Claude Cowork/Code, OpenAI Codex) to prototype, validate, and accelerate product work, with a bias toward iterating quickly over long up-front specification
Working knowledge of natural language processing (NLP), machine learning (ML), and the concepts behind model training, evaluation, and accuracy measurement (precision, recall, F1, inter-annotator agreement)
Ability to understand business requirements and translate them into AI-powered product capabilities
Experience with data-intensive, enterprise-level applications, including multi-tenancy, enterprise authentication, and user management concerns
Prior product management experience in an agile development environment, with strong familiarity with JIRA and the ability to break work into well-scoped epics and stories.
Exceptional verbal and written communication skills

Nice To Haves

Advanced degree such as MBA, MS, PhD, or MD from a reputed institution
Product management experience in healthcare technology companies
Prior experience working with complex healthcare data, including electronic health records, clinical notes, claims, and disease registries
Experience with clinical data annotation, chart abstraction, reference-standard creation, or human-in-the-loop AI workflows
Familiarity with healthcare data standards and vocabularies (e.g., OMOP, FHIR, CDA) and de-identification practices
Life sciences domain experience, specifically around observational research studies and disease-specific cohorts

Responsibilities

Own the vision, strategy, and roadmap, sequencing delivery across your product area
Partner with the users and cross-functional collaborators — annotators, annotation supervisors, clinical subject-matter experts, AI + data engineers, and customer success— to translate their needs into a coherent, scalable product that produces research-grade, defensible outputs
Champion the unifying product principles across every feature: transparency at every step, knowledge that compounds over time, “AI does the work; experts decide,” and design for scale through configurability rather than custom engineering
Work in an AI-native, prototype-first way — using LLMs (e.g., Claude, ChatGPT, Gemini) and modern building tools (e.g., v0, Claude Cowork/Code, OpenAI Codex) to spec and pressure-test ideas yourself, then ship thin slices, measure accuracy and throughput with users, and improve in tight loops rather than long waterfall cycles
Define and instrument success metrics — extraction accuracy (precision/recall/F1), inter- annotator agreement, throughput, and cost-per-dataset reduction — and use them to drive prioritization
Manage the product release process and develop launch materials in collaboration with marketing and sales