The Senior Product Manager is an individual contributor and a core member of the Data & AI Product Innovation (DAPI) Product Discovery team, responsible for owning the full product lifecycle for a complex and strategic domain of data and AI products. Reporting to the Director, Product Discovery, this role leads continuous discovery, defines requirements, drives stakeholder alignment, and ensures that engineering investment is directed at problems worth solving.

DAPI operates as a lean, high-performing team supporting multiple product domains simultaneously. The Senior Product Manager operates at the highest individual contributor level owing a cluster of complex, interconnected products while informally guiding the product practice and contributing to the development of less experienced team members. You must be capable of managing competing priorities, rapidly shifting context, and making sound product decisions with incomplete information.

This role requires strong analytical self-sufficiency. You will define what success looks like for your products, partner with Analytics Engineers and Data Scientists to measure it, and use data to drive your own prioritization and discovery decisions. You will work with DAPI's embedded Analytics Engineering and Data Science teams to define, measure, and interpret product outcomes — bringing the domain context and analytical direction that makes that collaboration effective.

You will work closely with all users from all business verticals, data and software engineering teams, data science and AI teams, as well as senior leadership — applying design thinking principles to uncover real user needs and translate them into product solutions. You are the voice of the user within the DAPI team and the voice of the team to the business.

Product Discovery & Validation

• Lead continuous discovery for your product domain — problem framing, assumption mapping, user interviews, and rapid validation.
• Reduce risk across four dimensions before engineering investment: value, usability, feasibility, and viability.
• Engage directly with business users to uncover unmet needs, workflow friction, and high-value opportunities.
• Translate ambiguous business problems into well-scoped, testable product hypotheses.
• Validate product concepts through lightweight prototypes, storyboards, or data experiments before committing to build.

Product Strategy & Roadmap Ownership

• Own the product roadmap for your assigned domain — balancing quick wins, strategic investments, and technical debt.
• Prioritize using evidence from users, data, and business goals — defend prioritization decisions clearly.
• Define and communicate outcome-focused product goals that align with DAPI’s strategic objectives.
• Maintain a living backlog that reflects current understanding, not just accumulated requests.

Requirements & Delivery Partnership

• Author clear, well-structured product requirements, user stories, and acceptance criteria.
• Partner with Engineering and Architecture throughout delivery to resolve ambiguity, make trade-off decisions, and keep work moving.
• Participate actively in Agile/SCRUM ceremonies — sprint planning, backlog refinement, reviews, and retrospectives.
• Work closely with Delivery Management to track progress, surface risks, and communicate status to stakeholders.
• Validate delivered features against acceptance criteria and user intent before release.

AI Product Ownership

• Lead discovery and requirements definition for AI and machine learning product features within your domain.
• Understand when AI is the right solution and when it is not.
• Define human-in-the-loop requirements, explainability expectations, and trust signals for AI-powered features.
• Partner with Data Science to translate model capabilities into user-centered product experiences.
• Design for AI-specific risks: bias, uncertainty, user over-reliance, and failure modes.

Analytics & Measurement

• Define success metrics and KPIs for every product initiative before development begins.
• Partner with Analytics Engineers to instrument features, build product health dashboards, and monitor adoption.
• Conduct post-go-live analyses to assess whether shipped products achieved intended outcomes.
• Use data independently to interrogate product performance and form your own hypotheses.
• Proactively identify underperformance or emerging user needs through ongoing monitoring.

Stakeholder Engagement & Communication

• Build strong working relationships with stakeholders across all divisions.
• Communicate product decisions, trade-offs, and outcomes clearly to both technical and non-technical audiences.
• Manage stakeholder expectations actively.
• Represent user needs in cross-functional discussions, including with senior leadership.

Education:

Bachelor’s degree required in Business, Computer Science, Information Systems, Data Science, or a related field.

Experience:

• 7 + years of product management experience in a technology, data, or digital product environment, with demonstrated progression in scope and complexity.
• Demonstrated experience independently leading end-to-end product discovery and delivery for complex, multi-stakeholder products — not just backlog management.
• Hands-on experience defining and measuring product KPIs — including working directly with data to assess product performance.
• Proficiency in data analysis to validate assumptions and investigate product questions.
• Experience working in Agile/SCRUM environments with cross-functional delivery teams.
• Experience with modern product tools: Azure DevOps, Confluence, Figma, or equivalent.
• Experience in healthcare, life sciences, or another regulated industry strongly preferred.
• Exposure to AI/ML product development — understanding of model lifecycle, data dependencies, and user trust considerations.

Licenses:

• Certified Scrum Product Owner (CSPO)
• Product Owner/Product Manager
• Design Thinking certification, or equivalent Agile/product methodology credentials

Knowledge:

• Modern product management: continuous discovery, outcome-driven roadmaps, assumption testing, lean experimentation.
• Agile/Scrum delivery practices and how discovery and delivery teams interact.
• Data fundamentals: relational data models, SQL, dimensional warehousing, and analytics platform concepts.
• AI/ML product development: use case identification, human-in-the-loop design, model evaluation, and responsible AI principles.
• Healthcare or regulated industry context — how compliance, clinical workflow, and operational constraints shape product decisions.
• User research methods: interviews, observation, usability testing, and synthesis techniques.

Skills:

• Cultural competency and the ability to communicate effectively in a culturally sensitive manner with both individuals and groups from diverse backgrounds.
• Problem framing — structuring ambiguous problems into clear, testable product questions.
• Requirements authoring — writing user stories and acceptance criteria that are unambiguous and testable.
• Analytical self-sufficiency — SQL, dashboard consumption, and data interpretation without analyst support.
• Communication — tailoring messages and detail level to engineering teams, business stakeholders, and executive audiences.
• Prioritization — making and defending evidence-based tradeoff decisions under resource and time constraints.
• Facilitation — leading discovery sessions, stakeholder workshops, and sprint ceremonies.

Abilities:

• Operate with autonomy across multiple products and priorities simultaneously.
• Hold the line on scope and quality while maintaining strong stakeholder relationships.
• Make sound product decisions with incomplete information and escalate appropriately when needed.
• Learn new business domains quickly — becoming a credible domain expert without years of background.
• Challenge existing workflows and advocate for better approaches while maintaining trust.
• Serve as a product practice resource for peers — sharing methods, patterns, and domain knowledge that raise the team’s overall capability.
• Work effectively in a lean team where individual contribution directly drives outcomes.

Any combination of education, training, and experience equivalent to the requirements above that has supplied the necessary knowledge, skills, and experience to perform the essential functions of the job.

For applicants who will perform this position in Westchester County, the proposed annual salary is $140,000.00 to $150,000.00 per year.  For applicants who will perform this position outside of New York City or Westchester County, salary will reflect local market rates and be commensurate with the applicant’s skills, job-related knowledge, and experience.

Founded in 1964, New York Blood Center (NYBC) has served the tri-state area for more than 60 years, delivering 500,000 lifesaving blood products annually to 150+ hospitals, EMS and healthcare partners. NYBC is part of New York Blood Center Enterprises (NYBCe), which spans 17+ states and delivers one million blood products to 400+ U.S. hospitals annually. NYBCe additionally delivers cellular therapies, specialty pharmacy, and medical services to 200+ research, academic and biopharmaceutical organizations. NYBCe’s Lindsley F. Kimball Research Institute is a leader in hematology and transfusion medicine research, dedicated to the study, prevention, treatment and cure of bloodborne and blood-related diseases. NYBC serves as a vital community lifeline dedicated to helping patients and advancing global public health. To learn more, visit nybc.org. Connect with us on Facebook, X, Instagram, and LinkedIn.