Digital Product Analytics & Experimentation Specialist

The Charles Schwab Corporation

Westlake (TX)

On-site

USD 120,000 - 160,000

Full time

10 days ago

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Job summary

The Charles Schwab Corporation in Westlake, TX is seeking a Digital Product Analyst to lead measurement, analytics, and reporting across experimentation and personalization. You will define KPIs, build dashboards, and translate results into strategic decisions across product, analytics, and technology teams.

You will establish scalable analytics practices, optimize audience and model performance, and drive data-informed roadmaps for digital experiences.

Qualifications

Bachelor’s degree in statistics, data science, mathematics, economics, computer science, business analytics, or related field.
5+ years of experience in data analysis, digital analytics, product analytics, experimentation analytics, decision science, or related discipline.
Demonstrated experience designing measurement frameworks, defining KPIs, and building dashboards or recurring performance reporting.
Hands-on experience analyzing controlled experiments and applying statistical concepts such as hypothesis testing, confidence intervals, power, sample size, and minimum detectable effect.
Proficiency with SQL and at least one analytical programming language, preferably Python, for data extraction, transformation, validation, automation, or statistical analysis.
Experience working with APIs and combining data from multiple platforms or enterprise sources.
Ability to translate complex data into concise insights, recommendations, and compelling narratives for business and technical stakeholders.
Proven ability to lead cross-functional work, build consensus, and influence outcomes in a highly matrixed organization.
Strong attention to detail, documentation, organization, and analytical quality.

Responsibilities

Own the measurement strategy for experimentation and personalization, including program health, platform utilization, adoption, outcomes, and business impact.
Define consistent metrics, KPIs, measurement frameworks, calculation methods, and reporting standards across programs and participating teams.
Build and maintain dashboards, recurring reports, and executive-ready portfolio views that translate activity and results into decisions and priorities.
Develop approaches to assess incremental impact and ROI, while clearly documenting assumptions, limitations, and data quality considerations.
Identify trends, gaps, and opportunities that shape program strategy, capability roadmaps, and investment decisions.
Partner with product and business teams to define testable hypotheses, primary and secondary metrics, guardrails, sample-size and duration assumptions, and analysis plans.
Analyze A/B tests, multivariate tests, feature experiments, and other controlled evaluations using appropriate statistical methods.
Monitor live experiments for data quality, allocation, instrumentation, and performance issues without compromising test integrity.
Translate completed test results into clear recommendations, reusable insights, and implications for product and experience roadmaps.
Establish scalable standards, templates, and best practices for experiment design, measurement, reporting, and knowledge sharing.
Define how personalized experiences, audiences, decision rules, recommendations, and journeys will be measured across digital channels.
Lead analysis of audience reach, eligibility, utilization, engagement, conversion, and downstream client or business outcomes.
Provide analytical input to audience design, model performance, test-and-control strategies, and ongoing optimization of decisioning approaches.
Manage or coordinate audience creation and lifecycle practices, including definitions, documentation, validation, refresh expectations, and performance monitoring.
Create a feedback loop that uses experience outcomes to inform model, audience, content, and journey improvements.
Integrate and reconcile data from experimentation, digital analytics, personalization, audience, and business reporting platforms using SQL, Python, APIs, and enterprise data tools.
Identify instrumentation, taxonomy, identity, data quality, and source-integration gaps that affect measurement or decisioning.
Define program-level data requirements and partner with Schwab Data and technology teams to prioritize data ecosystem improvements.
Establish traceable, repeatable, and well-documented analytical workflows that can scale across business units and digital channels.
Create and maintain data definitions, source documentation, quality checks, and reporting controls appropriate for a highly governed environment.
Serve as the central analytics partner for Experimentation and Personalization, coordinating across business-unit analysts, product managers, data scientists, engineers, strategy teams, and platform partners.
Build alignment on shared metrics, standards, ownership, and priorities while respecting the needs of individual use cases and business areas.
Communicate complex analytical concepts, tradeoffs, and findings with clarity to technical, business, and executive audiences.
Coach partners on measurement and analytical best practices and promote disciplined, client-focused use of data.
Operate independently through ambiguity, balancing hands-on analysis with program structure, governance, and long-term capability development.