Principal Data Product Manager

Role Description

As Principal Product Manager, Data & Insights, you will define how data powers products, customer experiences, analytics, recommendations, and analytical AI capabilities. You will set the strategy, priorities, and roadmap for how data is captured, modeled, measured, exposed, and leveraged across the platform, turning it into capabilities that improve customer outcomes, sharpen differentiation, and unlock new growth.

The next generation of software products will be differentiated by how effectively they leverage data. This role defines how data becomes a reusable platform capability, powering better products, better customer experiences, and future innovation across PayNearMe.

Data & Insights Strategy

• Define the long-term vision for data as a strategic product and platform capability.
• Identify opportunities to improve products and customer experiences through data.
• Prioritize investments across data products, insights, analytics, recommendations, and analytical AI capabilities.
• Set roadmap priorities that keep data strategy aligned to business goals.

Platform Data Capabilities

• Define reusable data capabilities that scale across products and experiences.
• Drive accessibility, governance, discoverability, and common business definitions for core data assets.
• Establish a consistent approach for modeling, measuring, and exposing data across the platform.
• Enable teams to build on shared data assets rather than one-off solutions.

Customer-Facing Analytics & Recommendations

• Identify and prioritize opportunities for customer-facing insights, recommendations, and analytics experiences.
• Embed data-driven capabilities into existing products.
• Evaluate and pursue new data-driven product opportunities.

Analytical AI & Automation

• Own the roadmap for analytical AI capabilities that turn raw data into decisions.
• Define the data, measurement, and product requirements behind AI-enabled experiences and workflow automation.
• Shape how data improves decision-making, automation, and customer outcomes.
• Translate emerging technology capabilities into real customer and business value.

What Success Looks Like

• Data operates as a reusable platform capability across multiple products and experiences.
• Product teams consistently discover, access, and trust core data assets.
• Data-driven insights and recommendations are embedded within customer experiences.
• Data investments tie directly to customer outcomes and business impact.
• New opportunities for differentiation and growth emerge through data.
• The company has a clear strategy for data across analytics, recommendations, automation, and AI.

Qualifications

• 10+ years in Product Management, with substantial experience in data-intensive, platform, analytics, or AI-enabled products.
• Track record defining, launching, and scaling products powered by data, analytics, recommendations, or machine learning.
• Deep understanding of how data is collected, modeled, governed, measured, and exposed through products and platforms.
• Command of the technical landscape across data engineering, analytics, machine learning, and software engineering.
• Ability to translate complex data capabilities into simple, valuable customer experiences.
• Experience defining product strategy in environments where data is a core competitive advantage.
• Systems thinker who identifies reusable capabilities that benefit multiple products.
• Comfortable navigating ambiguity and shaping new product categories.
• Strong communication, influence, and executive stakeholder management skills.
• Experience with data products, analytics platforms, recommendation systems, AI-powered experiences, or workflow automation.
• Familiarity with modern data platforms and concepts such as semantic layers, governance, APIs, data sharing, and AI/ML ecosystems.
• Experience in fintech, payments, or other data-rich, regulated industries.

Requirements

• Naturally curious and energized by data.
• Finds patterns, connections, and opportunities within complex datasets.
• Equally fluent in customer problems, business strategy, and technical architecture.
• Sees data as a strategic product and platform capability, not a reporting function.
• Balances long-term platform thinking with practical execution.
• Connects data investments to customer value, differentiation, and business outcomes.

Benefits

• Competitive salary and benefits with growth-company options grant.
• Fast-paced and professional work culture.
• Stock options with standard startup vesting - 1 year cliff; 4 years total.
• $50 monthly communication expense stipend to go towards your phone/internet bill.
• $250 stipend to enhance your WFH setup.
• Reimbursement for peripheral equipment: monitor (up to $400), keyboard and mouse (up to $200).
• Premium medical benefits including vision and dental (100% coverage for employees).
• Company-sponsored life and disability insurance.
• Paid parental bonding leave.
• Paid sick leave, jury duty, bereavement.
• 401k plan.
• Flexible Time Off (our team members typically take off ~3-4 weeks per year).
• Volunteer Time Off.
• 13 scheduled holidays.