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Job Category

Data

Job Details

About Salesforce

We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place.

The Internal Audit Organization is an independent and objective function that evaluates and provides recommendations to enhance the effectiveness, efficiency, and scalability of Salesforce processes, information systems, and the underlying governance, risk management and internal control environment. This function reports administratively to the President and Chief Operating and Financial Officer and directly to the Audit and Finance Committee of the Company’s Board of Directors.

We are seeking a highly skilled and self-motivated Internal Audit Data Analytics (IADA) Technical Manager to drive digital innovation and audit analytics capabilities within our internal audit function. This role will lead the technical execution of audit analytics, using AI/ML, predictive modeling, and sophisticated data technologies to further advance our capability. The IADA Technical Manager will be responsible for hands-on AI/ML development, automation of audit processes, and data-driven risk insights, while collaborating with multi-functional teams to advance audit analytics program. This role is hybrid and works in the Indy, Atlanta or Dallas office 3 days a week.

Key Responsibilities

• Lead hands-on development and deployment of AI/ML-driven audit analytics solutions, including predictive and generative AI models for risk detection and anomaly identification.

• Manage the technical lifecycle of audit analytics solutions—from data acquisition, preparation, modeling, validation, and productization to continuous monitoring and optimization.

• Build and automate audit analytics solutions using technologies such as Salesforce Data Cloud, Agentforce, Tableau, Snowflake, AWS SageMaker, Python, and Apache Airflow.

• Develop AI-powered risk models that enhance fraud detection, control testing, and anomaly detection in audit processes.

• Create interactive and real-time dashboards in Tableau to visualize AI/ML model outputs and key audit insights.

• Manage the audit tenancy in the ML platform, ensuring secure and compliant use of AI/ML tools while providing internal support and training on data analytics capabilities.

• Partner with other teams to translate business risks into data-driven audit analytics solutions.

• Conduct thorough model validation, testing, and explain-ability assessments to ensure AI/ML models meet ethical and regulatory standards.

• Provide technical leadership, mentorship, and advisory support to internal teams on using data analytics and AI/ML methodologies.

• Complete projects in a fast-paced, time-sensitive environment, effectively managing multi-functional workstreams.

Required Experience & Qualifications

• Proven hands-on experience in AI/ML development (e.g., model building, training, deployment, and monitoring) within audit, risk, compliance, or related fields.

• Strong understanding of risk, controls, and business process concepts, with the ability to integrate AI-driven insights into audit methodologies.

• Bachelor's degree in a quantitative field (e.g., Data Science, Computer Science, Engineering, Mathematics, Statistics, or Operations Research) or equivalent experience. A master's degree or relevant certifications are a plus.

• 7+ years of experience in audit data analytics, risk analytics, or a related field, including 2+ years in a managerial role and experience in a technology or fast-paced industry.

• Hands-on expertise in AI/ML tools and cloud-based platforms, including AWS SageMaker, Python, SQL-based ETL tools, and REST APIs.

• Experience with Salesforce ecosystem technologies (e.g., Salesforce CRM, Data Cloud, Agentforce, Mulesoft) and data v