Data Analytics Project Manager

Description

Data Analytics Project Manager - Internal Audit

Position Summary

We are seeking a highly motivated  Data Analytics Project Manager  to help advance Internal Audit's use of data, automation, and emerging technology.

The Audit Data Analytics Project Manager will partner with audit teams to design and execute data-driven audit solutions, including population-based testing, exception analysis, continuous auditing, and other advanced analytics approaches. The role will support multiple businesses and functions across the organization and interact regularly with Audit, Compliance, Risk Management, Technology, Finance, and business-area stakeholders.

In addition to delivering individual analytics projects, the Project Manager will help develop  repeatable, scalable, and reusable analytics capabilities t  hat improve audit coverage, quality, efficiency, and insight.

The position will also provide informal coaching and development to team members, review analytical work and related documentation, communicate project status and results to stakeholders, and contribute to the continued evolution of Internal Audit's analytics capabilities.

Key Responsibilities

The Audit Data Analytics Project Manager will:

+  Lead the design, development, execution, and implementation of data analytics solutions supporting audit planning, testing, continuous auditing, and risk identification.

+  Partner with audit teams during planning to identify opportunities for full-population testing, exception-based analysis, continuous auditing, automation, and other data-driven audit approaches.

+  Develop and enhance reusable and scalable analytics solutions, reducing reliance on one-time analysis and improving consistency across audit engagements.

+  Develop, maintain, and improve continuous auditing solutions, including recurring population analysis, exception identification, trend analysis, and delivery of testing results.

+  Apply appropriate techniques to evaluate data completeness, accuracy, lineage, transformation logic, and fitness for audit purposes and document analytics work to support audit reliance.

+  Translate audit objectives, risks, and business problems into practical data and technology solutions.

+  Analyze large and complex datasets to identify exceptions, anomalies, patterns, trends, and other insights relevant to audit objectives.

+  Identify opportunities to appropriately use automation, artificial intelligence, and emerging analytics capabilities to improve audit effectiveness and efficiency.

+  Ensure analytics activities and supporting documentation meet departmental and professional standards and established timelines.

+  Review analytical work performed by others and provide coaching, technical guidance, and quality review.

+  Build strong relationships with Audit, Technology, Risk, Compliance, Finance, and business partners.

+  Stay current on developments in data analytics, automation, AI, visualization, and audit technology and evaluate practical applications within Internal Audit.

Basic Qualifications

+  Bachelor's degree in Business Analytics, Data Analytics, Data Science, Computer Science, Management Information Systems, Accounting, Finance, or related discipline

+  4+ years of experience in data analytics, audit analytics, technology, risk management, internal audit, or a related field

Preferred Qualifications

+  Experience translating business, risk, or audit objectives into data-driven solutions

+  Experience performing or supporting data validation, analytical testing, or population-based analysis

+  Strong analytical, critical-thinking, problem-solving, and communication skills

+  Demonstrated experience using SQL to analyze large and complex datasets

+  Experience working in Internal Audit, Risk Management, Compliance, banking, financial services, or another highly regulated industry

+  Experience developing population-based, exception-based, or continuous analytics

+  

Experience with Python or other data analysis/scripting languages

+  

Experience with business intelligence and visualization tools such as Tableau

+  

Experience with automation, artificial intelligence, or emerging analytics technologies

+  Experience designing repeatable or reusable analytical solutions

+  Understanding of data quality, lineage, governance, and validation concepts

+  Knowledge of banking processes, risks, regulations, and regulatory expectations

+  Strong project management and stakeholder-management skills

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