Internal Audit Data Analytics - Manager

Internal Audit Data Analytics – Manager

Company	Salesforce
Location	Indianapolis, IN, USA, Dallas, TX, USA, Atlanta, GA, USA
Salary	$Not Provided – $Not Provided
Type	Full-Time
Degrees	Bachelor’s, Master’s
Experience Level	Senior, Expert or higher

Proven hands-on experience in AI/ML development (e.g., model building, training, deployment, and monitoring) within audit, risk, compliance, or related fields.
Solid 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 visualization tools such as Tableau.
Experience with programming skills, including SQL, Python, Jupyter Notebooks, and workflow automation tools like Apache Airflow.
Excellent communication skills with the ability to communicate technical concepts to non-technical partners and drive business impact.
Demonstrated ability to lead and mentor teams, fostering a data-driven audit culture.

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.
Lead 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 explainability 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.