Senior Business Experience & Planning Advisor – Customer Data Forensics

Role Overview

• Serve as a subject matter expert (SME) for enterprise customer data concepts including customer identity, householding, customer hierarchies, contact data, consent/preferences, and customer attributes.
• Drive customer data definition alignment (business glossary, critical data elements, metadata), ensuring consistent meaning and usage across platforms and lines of business.
• Contribute to customer data strategy and roadmap, identifying opportunities to modernize customer data capabilities and reduce fragmentation.
• Execute customer data quality management practices: profiling, monitoring, rule definition, threshold tuning, and performance reporting.
• Lead investigation of data anomalies and recurring defects using structured root cause analysis; coordinate remediation with upstream/downstream partners.
• Implement scalable controls and preventive measures (e.g., validation rules, reconciliation checks, exception handling, automation) to reduce repeat issues.
• Partner with analytics and data science teams to translate business problems into data requirements, analytically ready datasets, and reusable features (e.g., customer identity, household, relationship, and behavioral attributes).
• Support model development and monitoring by improving data completeness, stability, and explainability; document assumptions, transformations, and known limitations for appropriate use.
• Enable business decisioning use cases by defining customer data inputs for segmentation, targeting, credit/marketing decisioning, personalization, and next-best-action solutions.
• Establish fit-for-purpose data quality checks for analytic pipelines (distribution shifts, outliers, freshness, leakage risks) and coordinate remediation when thresholds are breached.
• Collaborate with partners to develop KPIs and measurement approaches that connect data improvements to business outcomes (e.g., conversion, retention, risk performance, operational efficiency).
• Support customer data governance routines including stewardship forums, issue/decision logs, and control evidence management to enable consistent, trusted use of customer data across reporting, analytics, and decisioning.
• Ensure customer data processes and controls align to risk, audit, privacy, retention, and regulatory requirements while supporting responsible innovation and scalable analytic consumption.
• Produce leadership-ready reporting on customer data risk posture, control health, remediation progress, and key metrics; highlight impacts to critical reporting, models, and decision solutions.
• Partner with data engineering and product teams to define requirements for customer data solutions (MDM/EDS/APIs/data lake), including onboarding, lineage, analytic consumption patterns, and performance/availability needs.
• Support design and operationalization of “trusted” customer data products and feature sets (e.g., curated views, golden records, identity/household features), including documentation, data contracts, and consumption guidance.
• Enable analytics, operations, and customer-facing teams by improving accessibility to reliable customer datasets and features, advising on proper usage, and accelerating time-to-insight/time-to-decision.
• Act as a connector across business, operations, risk, and technology—translating business needs into data requirements and actionable delivery plans.
• Mentor analysts/junior data stewards and promote standards, playbooks, and repeatable practices.
• Influence without authority through clear narratives, fact-based recommendations, and proactive stakeholder engagement.

Requirements

• Experience with Master Data Management (MDM), customer identity resolution, probabilistic matching, or householding solutions.
• Familiarity with data governance frameworks and tools (e.g., Collibra/Alation, Archer/GRC tools, data cataloging/lineage platforms).
• Experience supporting regulatory programs, MRAs, audit readiness, and control evidence practices.
• Experience supporting analytics and data science workflows (feature engineering, cohort/segment analysis, model inputs/outputs) and translating business decision needs into data solutions.
• Familiarity with decisioning and measurement practices (e.g., segmentation strategies, champion/challenger testing, experimentation, KPI design) and working with stakeholders to evaluate impact.
• SQL proficiency and experience working in data lake / warehouse environments (cloud and/or on-prem).
• Background in financial services data management or other highly regulated environments.

Tech Stack

• Cloud
• SQL

Benefits

• medical/prescription drug coverage (with a Health Savings Account feature)
• dental and vision options
• employee and spouse/child life insurance
• short and long-term disability protection
• 401(k) with PNC match, pension and stock purchase plans
• dependent care reimbursement account
• back-up child/elder care
• adoption, surrogacy, and doula reimbursement
• educational assistance, including select programs fully paid
• a robust wellness program with financial incentives
• maternity and/or parental leave
• up to 11 paid holidays each year
• 9 occasional absence days each year, unless otherwise required by law
• between 15 to 25 vacation days each year, depending on career level; and years of service