Product Manager
Listed on 2026-01-16
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IT/Tech
Data Analyst, Data Science Manager
Deep Intent is leading the healthcare advertising industry with data-driven solutions built for the future. From day one, our mission has been to improve patient outcomes through the artful use of advertising, data science, and real-world clinical data. For more information visit, .
What You’ll DoDeep Intent is seeking a Product Manager, Outcomes & Measurement to help build and scale our outcomes-driven measurement products. This role is focused on delivering closed-loop measurement capabilities that connect advertising exposure to real-world healthcare outcomes, such as prescription lift and audience performance. In this role, you will work on products that sit at the core of how Deep Intent proves value to healthcare advertisers.
You will collaborate closely with Product Leadership, Engineering, Data Science, Analytics, Clinical Insights, UX, and Client Strategy to operationalize measurement methodologies into scalable, repeatable products used by brands and agencies.
- Own scoped areas of the outcomes and measurement roadmap, supporting the delivery of closed-loop measurement capabilities.
- Translate measurement use cases and customer requirements into clear product requirements, user stories, and acceptance criteria.
- Contribute to defining product success metrics tied to measurement adoption, reliability, and customer impact.
- Support the development of measurement products that connect ad exposure to real-world healthcare outcomes using privacy-safe data.
- Work closely with Data Science and Clinical Insights to operationalize and optimize methodologies.
- Help ensure measurement outputs are statistically valid, clearly explained, and aligned with customer expectations.
- Contribute to product requirements that allow measurement outputs to inform campaign optimization and planning.
- Support the validation and iteration of measurement signals used in reporting and optimization workflows.
- Partner with Analytics and Engineering to ensure outcomes data is usable, timely, and actionable.
- Work closely with Engineering to define feature requirements, dependencies, and delivery sequencing for measurement initiatives.
- Develop a working understanding of how data pipelines, identity resolution, and privacy constraints impact measurement products.
- Support initiatives to improve reliability, scalability, and repeatability of measurement workflows.
- Partner with UX to ensure measurement workflows, reporting, and outputs are intuitive for both technical and non-technical users.
- Collaborate with Sales and Client Strategy teams to support customer-facing measurement narratives, documentation, and enablement.
- Work with Analytics and Clinical Insights teams to incorporate feedback and support data quality and issue resolution.
- Communicate product requirements, tradeoffs, and timelines clearly to internal stakeholders.
- Assist in explaining measurement methodologies and results to non-technical audiences.
- Support product demos, training materials, and internal enablement related to outcomes measurement.
- 3+ years of product management experience with direct ownership or contribution to a measurement product.
- Experience working on healthcare advertising measurement, such as:
- Closed-loop measurement platforms
- Claims-based or outcomes-based analytics products
- Healthcare AdTech or real-world evidence tools
- Strong understanding of measurement concepts, including lift, incrementality, and control vs. exposed study design.
- Experience partnering closely with Data Science, Analytics, and Engineering teams.
- Ability to translate complex measurement logic into clear product requirements and user-facing workflows.
- Strong written and verbal communication skills.
- Familiarity with pharmacy or medical claims data and their use in advertising measurement.
- Experience supporting customer-facing measurement deliverables or reporting products.
- Background in analytics, statistics, economics, or experimentation.
- Experience operating in privacy-sensitive, regulated data…
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