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Job Description & How to Apply Below
About Doceree
Doceree is the only Healthcare OS in the pharma ecosystem. As the first global network of physician-only platforms for programmatic messaging, Doceree is transforming the digital communication landscape in the global healthcare industry. Doceree provides the most comprehensive solution to Healthcare and Life Sciences advertisers to reach their target audience in the most effective and efficient way through programmatic digital advertising.
Our Core Belief:
Technology can connect the fragmented healthcare ecosystem to deliver information when it is most needed to improve patients' outcomes.
We are expanding our footprints across the globe and enhancing our services, offering, and developing new products and solutions to address the unmet needs of the industry. Doceree is operating in 22 countries currently with offices in New York, India, and London.
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About the Job
Position Title:
Principal Product Manager — Data Science and AI
Department:
Product & Engineering
Job Scope:
India
Location:
Noida
Work Setting:
In Office
Why This Role Exists
Doceree is building Rep Twin an AI-powered platform that creates intelligent digital sales representatives for pharmaceutical companies. These AI agents engage Healthcare Professionals (HCPs) across voice, video, chat, and messaging channels, trained on brand-specific knowledge bases and deployed at scale across global markets.
The foundation is live. Now we need a Principal PM to own the next phase — expanding use cases, driving quality and correctness at scale, deepening vertical integrations, and establishing AI differentiation that makes Rep Twin the category leader in pharma AI engagement.
This is not a role where you inherit a stable product and optimise metrics. This is a role where you define what the product becomes, make hard prioritisation calls every week, and ship alongside a lean team of builders who release weekly.
Key Responsibilities
Product Strategy & Vision
- Define and maintain the product roadmap across a rolling horizon, making trade-off decisions across the five pillars above based on revenue impact, client feedback, and technical feasibility.
- Conduct competitive analysis across pharma AI engagement and identify positioning opportunities.
- Translate business priorities into a structured, weekly-shippable execution plan for a lean engineering team.
- Present roadmap, progress, and strategic direction to leadership, clients, and cross-functional stakeholders.
Product Development & Execution
- Lead the end-to-end product lifecycle — from problem framing and PRD authoring through to launch, measurement, and iteration.
- Write clear, engineering-ready specifications: PRDs, user stories, acceptance criteria, and system prompt templates for AI agent behaviours.
- Work directly with builders in weekly sprint cycles. This team ships large changes every week — you need to keep pace.
- Own the definition of "done" for every feature. If a use case isn't demo-ready, it hasn't shipped.
User Experience & Enablement
- Collaborate with design to deliver polished, intuitive experiences across the admin dashboard (deployment configuration, knowledge base training, analytics) and the end-user engagement layer (chat widget, voice calls, Whats App).
- Design onboarding flows that let new clients go from sign-up to live deployment with minimal friction.
- Create sales enablement materials: demo scripts, use case playbooks, and benchmark reports that the commercial team can use independently.
Data, Measurement & Optimisation
- Define KPIs for every product surface: use case conversion rates, training module completion and pass rates, chatbot engagement quality scores, latency percentiles, integration sync reliability.
- Build feedback loops from the Review Genie testing framework into product improvement cycles — every AI response that gets flagged should inform the next iteration.
- Use analytics to identify drop-off points, underperforming use cases, and expansion opportunities.
Stakeholder Management
- Serve as the primary product voice for the AI agent platform across sales, client success, and leadership.
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