Staff Business Data Analyst, Quality Management System

What you'll do

• Design measurement approaches for defect domains, including DPMO instrumentation and defect taxonomy.
• Build and maintain defect funnels to quantify volume, severity, and contribution to customer outcomes.
• Analyze large operational datasets using SQL and Python/R to isolate root causes of defects.
• Validate the impact of improvement initiatives using causal analysis, cohort comparisons, or pre-post testing.
• Own the end-to-end defect reduction loop from detection and root cause verification to initiative launch and validation.
• Deploy structured improvement methods like Lean, Six Sigma, and Kaizen to drive prioritized fixes.
• Build and maintain dashboards to surface defect signals and track outcome metrics for leadership decisions.
• Hold cross-functional partners accountable for quality outcomes using quantified evidence and structured escalation.

What we're looking for

• Bachelor's degree in a quantitative field or equivalent professional experience in operational analytics.
• 7+ years of experience in operational analytics, quality analytics, or continuous improvement roles.
• Proficiency in SQL and working fluency in Python or R for analyzing large operational datasets.
• Solid grounding in applied statistics, including distributions, hypothesis testing, and control charts.
• Experience with defect-based measurement frameworks (DPMO) and translating process defects into outcome-level impact.
• Experience in or strong familiarity with contact center environments, including BPO models and service operations.
• Working knowledge of structured improvement methods such as Lean, Six Sigma, and root cause analysis.
• Experience with causal inference, experimentation methods, or AI-based quality measurement systems (preferred).