Product Manager, Data Analytics & Insights

F & I Sentinel Llc•Dallas, TX

18h•Remote

About The Position

We are hiring a Product Manager to lead the strategy, governance, and evolution of enterprise data capabilities powering customer-facing products, operational intelligence, financial reporting, and scalable business decision-making. This role is responsible for improving the quality, consistency, trust, and usability of data across the organization while building customer-facing insights and reporting experiences. The role owns data as a strategic product, defining shared data foundations, governing metrics and schemas, and enabling scalable, data-driven capabilities across products and business functions. The Data Analytics & Insights Product Manager will operate at the intersection of Product, Data Engineering, Analytics, Finance, Compliance, Operations, and Customer Experience to ensure data is accurate, auditable, actionable, and aligned across internal and external systems.

Requirements

5+ years of experience as a Product Manager, with significant experience in data, analytics, or platform products
Demonstrated ownership of data-driven products, datasets, or reporting platforms.
Experience building data-driven products, analytics features, or reporting experiences
Hands-on experience working with data frameworks, schema definition, and multiple data sources
Strong systems thinking and comfort with integration-heavy product environments
Proven ability to operate in ambiguity and build net-new product experiences
Background partnering closely with platform, data, or infrastructure-focused teams
Strong written and verbal communication skills, including executive-level communication
Strong stakeholder management and cross-functional collaboration skills
Outcome-oriented thinking: focused on automation, efficiency, and visibility
Ownership and accountability: Takes responsibility for product decisions and their impact
Judgment under constraint: Makes thoughtful decisions balancing compliance, risk, speed, and value
Systems thinking: Understands how data flows across products, operational processes, customer experiences, and financial reporting
Curiosity and learning mindset: Seeks evidence, validates assumptions, and incorporates learning into future decisions
Clarity and transparency: Communicates intent, decisions, and tradeoffs openly and clearly
Collaborative leadership: Leadership built on trust and partnership

Nice To Haves

Experience in automotive finance or adjacent regulated industries is preferred
Experience working in compliance or risk-sensitive environments is preferred

Responsibilities

Own data product outcomes from discovery through delivery and adoption
Define and validate problems using data signals, customer context, and financial impact
Define and maintain a clear data product roadmap aligned to customer value and business priorities
Translate complex technical and analytical concepts into actionable business insights and customer value
Improve the consistency, accuracy, trust, and usability of data across customer-facing and internal systems
Partner with Data Engineering to define scalable data models, schemas, lineage, and transformation standards
Establish governance practices for data ownership, metric definitions, documentation, and quality standards
Support root-cause analysis and resolution of data inconsistencies, quality issues, and cross-system dependencies
Ensure customer-facing reporting experiences are accurate, scalable, intuitive, and trusted
Partner across Product, Engineering, Data, Finance, Compliance, Operations, and GTM teams to align priorities and drive execution
Influence data standards and best practices across product teams and organizational workflows
Communicate data strategy, roadmap priorities, risks, and outcomes clearly to leadership and stakeholders
Drive adoption of standardized data products and reporting capabilities across internal and external users
Partner with business teams to identify opportunities for automation, operational visibility, and improved decision-making
Establish monitoring and feedback loops to continuously improve data quality, product adoption, and business impact