Sr Manager, Optimization and Personalization

Pay range: USD $115,000.00 - $175,000.00 / Year

Your opportunity

At Schwab, you're empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us "challenge the status quo" and transform the finance industry together.

Schwab's Digital Retail organization leads the charge to deliver intuitive, client-centric experiences across web and mobile. We build with a "Through Clients' Eyes" mindset-putting the client at the center of every interaction and decision-so that each digital moment is simple, trustworthy, and personalized. We're recognized for strong retail brokerage experiences across platforms, and we're continuing to raise the bar with deeper experimentation and personalization capabilities.

Role Summary

We're seeking a Senior Manager to stand up, govern, and scale Digital Retail's experimentation (A/B & multivariate) and personalization capabilities. This leader will partner closely with product owners (manager/director level), engineering, data/analytics, and compliance to embed testing and targeted experiences into everyday delivery-creating standards, playbooks, and best practices that teams can self-serve. Think of this role as an internal consultant and program owner: Enabling teams to "learn by doing," while ensuring quality, statistical rigor, and regulatory guardrails.

What you'll do

Capability & Program Build

• Stand up a unified experimentation framework (metrics, audiences/segments, attribution, naming conventions) and define process to maintain a healthy flag/experiment space (dedupe, archive, lifecycle).
• Define governance for test quality, guardrails, and risk thresholds (e.g., traffic allocation, power/stop rules, data retention), aligned with FINRA/SEC marketing and communications expectations.
• Create reusable assets (standards, playbooks, decision trees, templates, example designs) for POs and engineers to operationalize experimentation and personalization at sprint pace.

• Coach Digital Retail product teams on hypothesis formation, experiment design, and analysis; review test plans, instrumentation, and results; and guide next-best actions. Help teams understand proper application of different test types (AB, MVT, Multi-armed bandit, etc).
• Embed experimentation into daily workflows using feature-flag driven testing and progressive rollouts (e.g., LaunchDarkly experiments tied to business metrics).
• Partner cross-functionally (UX, engineering, data science, marketing, operations, compliance) to align on cross-functional processes and oversee launch of targeted experiences that comply with privacy and accessibility standards.

• Operationalize rule-based and AI-assisted personalization for content and messaging across web/app, starting with recommended content modules and audience targeting; align with Schwab's personalization roadmap.
• Evaluate platform options- Assess current personalization tools and supporting infrastructure (data, content, etc), drive standards for integrations, data flows, and measurement; identify gaps and make recommendations that support long-term capability roadmap.
• Guide toward scale- Work closely with technology and product partners to progressively scale the tools and associated systems and architecture; support product team in scaling utilization as part of the product development life-cycle.
• Champion customer-obsessed personalization that deepens trust and relationships-consistent with Schwab's "Through Clients' Eyes" culture.

• Establish KPIs for program health and impact (e.g., test velocity, win rate, exposure discipline, lift in engagement/activation, compliance exceptions trend).
• Translate results for leadership-turn complex data into clear recommendations, portfolio views, and action plans that inform prioritization.

• 7-10+ years in digital product/marketing/optimization, with hands-on A/B/MVT testing and personalization across web/mobile; experience coaching teams and scaling programs.
• Experience with Schwab's digital retail processes and procedures either as an employee or contractor
• Practical expertise with feature flags and experimentation platforms (e.g., LaunchDarkly) and at least one enterprise testing/personalization tool (e.g., Optimizely, Adobe Target, LaunchDarkly, etc).
• Strong data literacy (KPIs, experiment power/significance, cohort/segment analysis) and the ability to connect outcomes to business metrics and client value.
• Proven success in highly matrixed environments-building consensus and working effectively with product, engineering, UX, analytics, and compliance.

• Financial services experience; understanding of SEC/FINRA marketing rules, data privacy (GDPR/CCPA), and accessibility (ADA/WCAG) implications for experimentation/personalization.
• Familiarity with digital analytics, segmentation and audience tools (CDP) for real-time audience targeting or similar stacks.
• Experience shaping playbooks and standards that teams can self-serve (vs. centralized COE delivery), with measurable adoption and impact.

• LaunchDarkly (flags, experiments, metrics, audiences; bandit and frequentist/Bayesian analysis; warehouse export).
• Optimizely (web/full-stack experimentation; personalization; bandits; analytics).

• 401(k) with company match and Employee stock purchase plan
• Paid time for vacation, volunteering, and 28-day sabbatical after every 5 years of service for eligible positions
• Paid parental leave and family building benefits
• Tuition reimbursement
• Health, dental, and vision insurance