Hybrid Digital Product Analyst - Experimentation

Charles Schwab

Austin (TX)

On-site

USD 110,000 - 160,000

Full time

2 days ago

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Benefits offered by this job

401(k) with company match

Employee stock purchase plan

Paid time off, volunteering, and sabat

Parental leave and family benefits

Tuition reimbursement

Health, dental, and vision insurance

Job summary

Charles Schwab in Austin is seeking a hands-on Digital Product Analyst to align program strategy with measurement, data, and execution across experimentation and personalization capabilities. You will build dashboards, define KPIs, assess A/B tests, and partner with product, analytics, data science, and engineering to drive scalable insights and informed decisions.

This role emphasizes cross‑functional collaboration, data quality, and governance while delivering actionable analytics that guide

Qualifications

Bachelor’s degree in statistics, data science, mathematics, economics, computer science, business analytics, or a related field, or equivalent practical experience
5+ years of experience in data analysis, digital analytics, product analytics, experimentation analytics, decision science, or a 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

Lead program measurement and insight across experimentation and personalization
Define metrics, KPIs, and reporting standards across programs
Build and maintain dashboards and executive portfolio views
Develop approaches to assess incremental impact and ROI with documented assumptions
Identify trends and opportunities shaping roadmap and investments
Partner with teams to define testable hypotheses and analysis plans
Analyze A/B, multivariate, and feature experiments
Monitor data quality and test integrity in live experiments
Translate results into actionable recommendations and reusable insights
Establish scalable standards for design, measurement, reporting, and knowledge sharing
Define how personalized experiences will be measured across channels
Analyze audience reach, eligibility, engagement, and outcomes
Provide input on model performance and optimization strategies
Coordinate audience creation, updates, and monitoring
Create feedback loops to inform improvements
Integrate and reconcile data from multiple sources using SQL, Python, APIs
Identify instrumentation and data gaps affecting measurement
Define program-level data requirements and coordinate with data/tech teams
Establish traceable analytical workflows that scale across channels
Create data definitions, documentation, and reporting controls
Serve as central analytics partner across the organization
Coordinate alignment on metrics and ownership
Communicate complex analytics to technical and executive audiences
Coach partners on measurement and best practices
Operate independently with governance and long-term capability building