Data Product Manager - Voice of Member

Photon; Boston (MA); On-site; USD 110,000 - 160,000; Full time

Job summary

Photon is seeking a Data Product Manager - Voice of Member to own the end-to-end product vision and roadmap for member feedback data products. You will lead discovery with Care, Membership, Digital, Club Ops, Merchandising, Supply Chain and Marketing to translate feedback into actionable experiences.

Responsibilities include prioritizing across surveys, sentiment, and closed-loop actions, and partnering with data engineering and analytics to deliver governed Databricks products.

Qualifications

• 5+ years of relevant product management, data product, analytics product or comparable experience.
• Bachelor's degree in a related field, or equivalent practical experience.
• Experience owning product vision, discovery, roadmap, prioritization, requirements, launch readiness, adoption and outcome measurement.
• Hands-on working knowledge of Databricks and modern lakehouse concepts, including governed data products, pipelines, semantic layers, data quality, lineage and self-service consumption.
• Ability to partner effectively with data engineering, analytics, data science, architecture, security, privacy and business teams.
• Ability to define product outcomes and KPIs, use evidence to make prioritization decisions and communicate complex data topics in business language.
• Working knowledge of agile product delivery, backlog management, dependency planning and change adoption.
• Working knowledge of Voice of Customer or Voice of Member language and strategy, including surveys, satisfaction, NPS, complaints, contact reasons, journey analytics, sentiment, text analytics, root-cause analysis and closed-loop action.

Responsibilities

• Defines and maintains the roadmap for Voice of Member data products and connects each investment to member experience, loyalty, service and operational objectives.
• Runs discovery with Member Care, Membership, Digital, Club Operations, Merchandising, Supply Chain and Marketing users to understand how member feedback is captured, interpreted and acted upon.
• Owns prioritization across surveys, satisfaction measures, complaints, contact reasons, service interactions, digital behavior, journey signals, sentiment, themes and closed-loop action capabilities.
• Defines common taxonomies, member-experience measures, business rules, quality thresholds, linkage requirements and acceptance criteria across feedback sources.
• Partners with data engineering, analytics and architecture to deliver governed Databricks products that integrate structured and unstructured experience signals.
• Evaluates and productizes appropriate AI/NLP capabilities such as topic classification, summarization, sentiment, emerging-issue detection and root-cause support, with human review and responsible-use controls.
• Designs products for action, not reporting alone, including ownership, routing, prioritization, traceability and measurement of business response.
• Plans adoption, training, communications, operating routines and support so insights are embedded in product, service and operational decisions.
• Measures performance through adoption, data trust, coverage, insight-to-action time and the member-experience outcome each product is intended to influence.

Skills

5+ years experience

Product management

Databricks

AI/NLP capabilities

Agile product delivery

Cross-functional collaboration

VoC/VoM language

Education

Bachelor's degree or equivalent

Tools

Databricks

Job description

Job Title :Data Product Manager - Voice of Member

Description for Internal Candidates

Key accountabilities / essential functions

• Defines and maintains the roadmap for Voice of Member data products and connects each investment to member experience, loyalty, service and operational objectives.
• Runs discovery with Member Care, Membership, Digital, Club Operations, Merchandising, Supply Chain and Marketing users to understand how member feedback is captured, interpreted and acted upon.
• Owns prioritization across surveys, satisfaction measures, complaints, contact reasons, service interactions, digital behavior, journey signals, sentiment, themes and closed-loop action capabilities.
• Defines common taxonomies, member-experience measures, business rules, quality thresholds, linkage requirements and acceptance criteria across feedback sources.
• Partners with data engineering, analytics and architecture to deliver governed Databricks products that integrate structured and unstructured experience signals.
• Evaluates and productizes appropriate AI/NLP capabilities such as topic classification, summarization, sentiment, emerging-issue detection and root-cause support, with human review and responsible-use controls.
• Designs products for action, not reporting alone, including ownership, routing, prioritization, traceability and measurement of business response.
• Plans adoption, training, communications, operating routines and support so insights are embedded in product, service and operational decisions.
• Measures performance through adoption, data trust, coverage, insight-to-action time and the member-experience outcome each product is intended to influence.

Scope, impact and decision making

Owns a cross-enterprise portfolio of Voice of Member data products serving leaders, analysts, product teams and operators. Makes roadmap, scope and sequencing decisions within the portfolio and recommends trade-offs involving shared member,

interaction and operational data. Impact is measured through adoption, quality, speed from signal to action and relevant member-experience outcomes.

Problem solving and complexity

Voice of Member data is distributed across channels, often unstructured and affected by context, selection bias and changing taxonomies. The role must avoid treating sentiment or survey data as complete on its own, connect feedback to behavioral and operational evidence and create explainable products that help teams act responsibly.

Leadership and influence

Leads through product vision, evidence, facilitation and influence rather than direct authority. Creates clarity across business, data, engineering, analytics, architecture, security and change-management partners; makes trade-offs visible; and holds the product team accountable for outcomes and adoption.

Key relationships and communication

• Member Care and Membership: feedback sources, service taxonomies, member journeys and closed-loop action.
• Digital Product, UX and Marketing: behavioral signals, journey research, experimentation and prioritization.
• Club Operations, Merchandising and Supply Chain: operational root causes, ownership and corrective actions.
• Data engineering, analytics, data science, architecture, privacy, security and governance: integration, NLP/AI methods, controls, quality and explainability.

Required qualifications

• 5+ years of relevant product management, data product, analytics product or comparable experience.
• Bachelor's degree in a related field, or equivalent practical experience.
• Experience owning product vision, discovery, roadmap, prioritization, requirements, launch readiness, adoption and outcome measurement.
• Hands-on working knowledge of Databricks and modern lakehouse concepts, including governed data products, pipelines, semantic layers, data quality, lineage and self-service consumption.
• Ability to partner effectively with data engineering, analytics, data science, architecture, security, privacy and business teams.
• Ability to define product outcomes and KPIs, use evidence to make prioritization decisions and communicate complex data topics in business language.
• Working knowledge of agile product delivery, backlog management, dependency planning and change adoption.
• Working knowledge of Voice of Customer or Voice of Member language and strategy, including surveys, satisfaction, NPS, complaints, contact reasons, journey analytics, sentiment, text analytics, root-cause analysis and closed-loop action.

Ways of working

• Keeping member and business value the deciding factor when scope pressure would cut it first.
• Building consensus across functions that have no reporting line to each other.
• Changing direction when evidence shows an approach is not working rather than continuing because of sunk cost.
• Holding commitments across concurrent workstreams and communicating early when constraints require a trade-off.
• Holding data products to ethical, privacy, security, quality and governance standards under pressure to ship.

Preferred qualifications

• Retail, wholesale club, service, contact-center, loyalty or digital customer-experience experience.
• Experience with survey platforms, contact-center analytics, digital analytics, journey analytics or experience-management platforms.
• Experience productizing NLP, GenAI or text-analytics capabilities with explainability, privacy and human-review controls.