Senior Auditor - Data Analytics

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Who we are:

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Join us to invest in yourself, your career, and the financial world.

The role:

SoFi is seeking a Sr Internal Auditor - Data Analytics to join the SoFi Internal Audit (IA) Department, reporting to Manager, Data Analytics, Internal Audit.  You will play a key role in advancing Internal Audit's (IA) data analytics capabilities by leading the design, development, and implementation of analytics solutions that support audit execution, continuous auditing, risk assessments, and departmental reporting.

This is a hands-on role that combines technical expertise, audit knowledge, and business partnership to enhance audit coverage, improve efficiency, and deliver data-driven insights across the organization.

What you’ll do:

• Lead the design, development, implementation, and maintenance of data analytics routines that support audit execution, continuous auditing, risk assessments, and departmental reporting.
• Partner with audit teams to identify opportunities to leverage analytics throughout the audit lifecycle, including planning, fieldwork, reporting, and continuous monitoring activities.
• Establish and maintain relationships with key data owners and stakeholders to improve data accessibility, quality, and understanding of business processes and data structures.
• Design and develop scalable analytics solutions that provide insights into risks, controls, operational performance, and emerging trends.
• Develop automated testing routines and continuous auditing capabilities that increase testing coverage, improve efficiency, and identify anomalies, outliers, patterns, and control weaknesses.
• Create dashboards, visualizations, and monitoring tools that communicate audit results, risk indicators, and continuous auditing outcomes to stakeholders.
• Contribute to the enhancement of Internal Audit's overall data strategy, analytics methodology, and automation framework.
• Collaborate with Internal Audit leadership and business partners to identify appropriate data sources and define analytics requirements.
• Produce recurring and ad hoc reports that measure audit program effectiveness, track analytics initiatives, and support Board and Audit Committee reporting.
• Represent Internal Audit on cross-functional initiatives, technology implementations, and special projects as needed.
• Stay current on emerging analytics, automation, and audit technologies and recommend opportunities for adoption within Internal Audit.

What you’ll need:

4+ years of experience in Internal Audit, Risk Management, Data Analytics, Data Science, or a related field, including experience supporting audit, risk, or compliance functions.

Strong hands-on experience with analytics and programming tools including SQL, Python, Alteryx, R, Excel, or similar technologies.

Experience developing data-driven audit testing, automation, and reporting solutions.

Strong experience with data visualization and business intelligence tools such as Tableau, Power BI, or similar platforms.

Working knowledge of internal and/or external auditing standards, risk management frameworks, and control environments.

Strong understanding of how data analytics can be applied within financial services, audit, risk management, or compliance functions.

Demonstrated ability to independently analyze large datasets, identify meaningful insights, and communicate findings effectively to stakeholders.

Experience leveraging data analytics within audit planning, risk assessments, continuous auditing, and audit execution activities.

Nice to haves:

Bachelor's degree in Data Science, Computer Science, Information Systems, Mathematics, Statistics, Business, Accounting, Finance, or a related field.

Professional certifications such as CIA, CISA, CPA, CRMA, CAMS, or data analytics-related certifications.

Experience building and maintaining data transformation workflows using DBT or similar tools.

Proficiency with Git/GitHub, code version control, peer reviews, and software development best practices.

Exposure to advanced analytics, machine learning, predictive modeling, or AI-enabled audit techniques.