Lead Data Analytics - Pittsburgh
3 hours ago
Job description
Job Description – Lead Data AnalyticsPosition Summary
Lead and manage a Fraud Monitoring Analytics team of ~5 data analysts.
Oversee delivery of fraud‑focused analytics projects across U.S. banking channels.
Act as primary client engagement lead, ensuring alignment on all fraud monitoring initiatives.
Provide technical and domain guidance across SQL, Python, PySpark, Spark, and big‑data environments.
Key Responsibilities
Fraud Monitoring & Domain Leadership
Partner with Fraud Strategy, Fraud Operations, Investigations, and Risk teams.
Deliver insights to improve fraud detection and reduce financial losses.
Engagement & Stakeholder Management
Serve as daily point of contact for client stakeholders.
Align on project scopes, timelines, priorities, and deliverables.
Team Leadership & People Management
Manage and mentor a team of ~10 fraud analytics professionals.
Oversee task assignments, priority alignment, and resource planning.
Develop team capabilities through training, feedback, and coaching.
Foster a culture of accuracy, accountability, and analytical rigor.
Project Delivery & Operational Excellence
Manage multiple fraud analytics workstreams simultaneously.
Establish project governance including planning, issue tracking, and documentation.
Ensure SLAs, quality standards, and delivery timelines are consistently met.
Oversee recurring fraud reporting, dashboards, and operational analytics.
Technical Oversight & Individual Contribution
Provide guidance on:
Advanced SQL,Python
PySpark SQL / Apache Spark
Data processing from Hadoop, Oracle, and large-scale data systems
Review solution design, fraud logic, and analytics code for quality and efficiency.
Support the team with hands-on contributions when needed.
End-to-End Fraud Analytics Workflow
Lead requirement gathering for fraud detection and alerting enhancements.
Oversee data extraction, wrangling, cleansing, and merging activities.
Required Skills & Qualifications
8+ years of experience in fraud analytics, risk analytics, or data analytics.
Proven experience leading a team of analysts in fraud or risk environments.
Strong project management background in fraud monitoring or financial crime analytics.
Expertise in SQL, Python, PySpark, Spark, and big-data environments (Hadoop, Oracle).
Strong understanding of U.S. banking fraud processes and alerting workflows.
Excellent communication and client-facing engagement skills.
Ability to create polished dashboards and executive-level presentations.
Experience with Account Opening, Deposits, Cards, or Transaction Monitoring fraud.
Preferred Qualifications
Experience supporting Fraud Strategy, Fraud Operations, or AML/Financial Crime teams.
Familiarity with fraud detection platforms or case management systems.
Project Management certifications (PMP, Agile, Scrum) preferred.
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