Senior Product Manager, Digital Retail – Digital Messaging Platform and Delivery Channels

Charles Schwab Inc.•Austin, TX

2d•$105,600 - $150,000•Onsite

About The Position

The Digital Retail Integrated and Core Experiences (DICE) organization drives consistent, streamlined digital experiences across Schwab’s platforms. Within DICE, the Digital Messaging team owns the platforms and channels that deliver secure, scalable, and reliable messaging to millions of clients and advisors. The Senior Product Manager, Digital Retail – Digital Messaging Platform and Delivery Channels (individual contributor) leads strategy for the Digital Messaging platform and delivery channels, with a focus on enabling and leveraging data to make informed decisions across the ecosystem. You will partner closely with product, technology, data and analytics, customer experience, and business teams to strengthen measurement, guide investment choices, and evolve scalable messaging capabilities.

Requirements

Bachelor’s degree or equivalent practical experience
8+ years of experience in product management, platform product management, analytics product management, data strategy, or a related discipline
Experience defining product strategy, measurable outcomes, and roadmaps for complex digital platforms or capabilities
Strong data and analytics fluency, with demonstrated ability to use qualitative and quantitative evidence to make and explain decisions
Experience building or leading scalable analytics, reporting, dashboard, and metrics frameworks
Experience leading cross-functional initiatives across business, product, technology, data, operations, risk, and customer experience teams
Ability to synthesize complex information and communicate recommendations, rationale, tradeoffs, progress, and risks to leadership and delivery teams
Comfort operating in loosely structured or uncertain situations, adapting the approach while providing clear direction and maintaining momentum
Systems thinking across platforms, channels, capabilities, and end-to-end client journeys
Ability to balance analytical precision, technical feasibility, risk, and enterprise scale
Experience with agile and lean product practices, including discovery, experimentation, backlog prioritization, dependency management, and outcome measurement

Nice To Haves

Experience with Tableau dashboard development and Tableau data modeling
Experience with SQL development in Oracle, BigQuery, or comparable environments
Experience with data analysis, data mining, reporting automation, ETL or data pipeline requirements, data quality and validation, analytics solution design, and metrics framework development
Knowledge of digital messaging platforms and delivery channels, including email, SMS, mobile push notifications, web messaging, mobile app messaging, or Message Center capabilities
Experience with journey analytics, experimentation frameworks, omnichannel measurement, or customer engagement platforms
Experience in financial services or another regulated environment
Familiarity with emerging technologies, including responsible use of AI-enabled analytics and automation, to improve insight, efficiency, or scalability

Responsibilities

Define and evolve the strategy and 12-month roadmap for the Digital Messaging platform and delivery channels, aligned to client needs, business priorities, and enterprise objectives
Establish clear outcomes, OKRs, key performance indicators, and success measures for platform, channel, and journey-level performance
Build scalable analytics, Tableau reporting, and measurement frameworks that enable data-driven decision-making across the Digital Messaging ecosystem
Translate complex data, client behavior, operational signals, and technical constraints into concise insights, strategic recommendations, and prioritization decisions
Lead development of dashboards, automated reporting, and reusable analytics solutions that improve visibility into messaging effectiveness
Define requirements for reporting automation, data quality, reconciliation, and validation in partnership with data and engineering teams
Support strategy and optimization across email, SMS, mobile push notifications, web messaging, and mobile app messaging, considering both individual channel performance and the end-to-end client journey
Lead cross-functional initiatives that align business, technology, data and analytics, risk, operations, and customer experience teams around strategic product outcomes
Own prioritization across new capabilities, channel enhancements, platform modernization, technical debt, defects, resiliency, and platform health initiatives
Coordinate dependencies and sequencing across multiple teams; surface risks early and ensure mitigation actions are clear and completed
Design and use experiments, hypotheses, and feedback loops to evaluate solution fit, learn quickly, and inform product direction
Balance technical tradeoffs across features and teams, adjusting priorities based on feasibility, architecture, dependencies, and sequencing impacts
Create clear product artifacts and decision documentation, including roadmaps, problem statements, business cases, measurement plans, and executive narratives
Build durable stakeholder relationships, facilitate complex decisions, and provide clear direction that keeps teams aligned and moving forward in ambiguous situations
Monitor industry, platform, data, and messaging trends and apply relevant insights to product strategy and capability planning
Establish shared AI workflows, standards, and playbooks that increase efficiency while preserving design quality, accessibility, and compliance
Partner with Product, Engineering, Risk, and Legal to pilot, evaluate, and responsibly scale AI‑enabled capabilities
Coach and mentor junior team members and peers on how and when to use AI effectively, building fluency, confidence, and ethical judgment
Use AI‑supported insights to inform prioritization, experience strategy, and decision making at both team and portfolio levels
Coach peers and junior team members in analytics fluency, product practices, documentation, and outcome-based decision-making