Senior Quality Analytics Lead — Service Excellence

Intuit, Inc.; United States; On-site; USD 151,000 - 204,000; Full time

Job summary

Intuit, Inc. in San Diego is seeking a Staff Quality Analyst to own the analytical engine for defect reduction across the Expert Network.

You design defect detection and quantification approaches, build defect funnels, size customer impact, and validate improvements with statistical rigor. This analytics role drives descriptive, diagnostic, and causal analysis on AI-scored conversation data spanning nearly all customer interactions, partnering with cross-functional teams to move resolution,

Qualifications

• Strong hands-on analytical skills: SQL proficiency and working fluency in Python or R for analysis of large operational datasets.
• Demonstrated experience turning operational data into prioritized, quantified improvement roadmaps — and validating whether the improvements worked.
• Experience with defect- or rate-based measurement frameworks (DPMO or equivalent) and translating process-level defects into outcome-level impact.
• Experience in complex, high-stakes service operations — contact centers, fintech, financial services, or expert/advisor networks.
• Demonstrated ability to build dashboards and analytical products that drive leadership decisions, including with AI-powered tools.
• Working knowledge of structured improvement methods (Lean, Six Sigma, root cause analysis) and experience using them to drive fixes from analytical findings.
• Experience driving accountability in matrixed organizations without direct authority over execution teams.
• Bachelor's degree in a quantitative field (Data Science, Statistics, Industrial Engineering, Operations Research, Economics, Business Analytics) or equivalent professional experience in operational analytics.

Responsibilities

• Design the measurement approach for assigned defect domains: define the defect, the opportunity base, and the DPMO instrumentation so every defect rate ladders directly to a customer outcome metric.
• Build and maintain defect funnels — quantifying defect volume, severity, and contribution to outcome degradation — and evolve the defect taxonomy as the operating environment changes.
• Prioritize the defect backlog analytically: rank initiatives by modeled customer impact, and defend the ranking with data when it is contested.
• Contribute to the continuous improvement of the quality measurement architecture itself — ensuring we measure the right things, validating that our measures stay true, and pressure-testing quality markers against outcome data.
• Analyze resolution, quality, sentiment, and customer friction signals across large operational datasets (SQL and Python/R against conversation-level and journey-level data) to identify defects and isolate root causes.
• Design the leading-indicator instrumentation beneath each outcome metric and monitor it for signal, drift, and regression.
• Validate initiative impact with appropriate rigor: pre/post analysis with controls, cohort comparison, or causal methods where the stakes demand them.
• Partner with analytics and data science teams to evaluate, adopt, and improve AI-native quality measurement.
• Own the operating loop for assigned defect domains: defect detected → root cause verified → initiative launched → outcome validated → loop closed.
• Deploy structured improvement methods — root cause analysis, Kaizen and rapid improvement events, value stream mapping, standard work.
• Translate analytical findings into technical solutions and roadmap commitments in partnership with systems and platform teams.
• Drive adoption and change management for the fixes, and embed the measurement disciplines that keep improvements from decaying.
• Hold dependencies — product, platform, routing, back-office — accountable for their share of customer friction using quantified evidence.
• Build and maintain the dashboards and reporting that surface defect signals, track outcome metrics, and support leadership decisions.
• Present defect reduction progress to senior stakeholders with clear data storytelling.
• Communicate uncomfortable findings credibly: when data contradicts the narrative, make the case with rigor.
• Use AI tools to accelerate defect detection, root cause analysis, and prioritization.

Skills

SQL proficiency

Python or R

Statistics

Data storytelling

Quality analytics

Causal inference

Education

Bachelor's degree in a quantitative field

Tools

Conversation Intelligence

Speech/Text Analytics

AI-native quality measurement

Job description

Intuit, Inc. in San Diego is seeking a Staff Quality Analyst to own the analytical engine for defect reduction across the Expert Network.

You design defect detection and quantification approaches, build defect funnels, size customer impact, and validate improvements with statistical rigor. This analytics role drives descriptive, diagnostic, and causal analysis on AI-scored conversation data spanning nearly all customer interactions, partnering with cross-functional teams to move resolution,