Staff Data Analyst - Internal Audit

The role:
SoFi is seeking a Staff Data Analyst – Internal Audit to join the SoFi Internal Audit (IA)
Department, reporting to the Manager, Data Analytics, Internal Audit. You will support the
development and execution of data analytics solutions that enhance audit planning, risk
assessments, audit testing, continuous monitoring, and departmental reporting.
This is a hands-on role for an analytical and curious professional who is interested in applying
data, technology, and business knowledge to support Internal Audit. You will work closely with
audit teams, data owners, and business stakeholders to analyze data, identify trends and
anomalies, improve audit efficiency, and communicate meaningful insights. The role will provide
opportunities to develop technical, audit, and stakeholder-management skills while contributing
to the continued growth of Internal Audit’s data analytics capabilities.

What you’ll do:
● Partner with audit teams to identify opportunities to use analytics throughout the audit
lifecycle, including planning, fieldwork, reporting, and monitoring activities.
● Assist with the development and enhancement of automated testing routines and
recurring monitoring processes.
● Create and maintain dashboards, visualizations, and reports that communicate audit
results, risk indicators, and monitoring outcomes.
● Work with data owners and stakeholders to understand business processes, data
structures, definitions, and data-quality considerations.
● Document analytics procedures, assumptions, data sources, testing logic, and results in
accordance with Internal Audit standards.
● Stay informed about emerging analytics, automation, and audit technologies and identify
opportunities to improve Internal Audit processes.
● Demonstrate curiosity and a willingness to learn emerging technologies, including
artificial intelligence, machine learning, automation, and advanced analytics.
● Explore and evaluate opportunities to responsibly apply AI and other emerging
technologies to improve audit planning, testing, monitoring, reporting, and operational
efficiency.
● Assist with developing, testing, and documenting AI-enabled or automated solutions that
support Internal Audit activities.

What you’ll need:
● 1+ years of experience in Data Analytics and Internal Audit, Risk Management, Data
Science, Compliance, or a related field.

● Experience using analytics and programming tools such as SQL, Python, Excel, Alteryx,
R, or similar technologies.
● Experience extracting, preparing, analyzing, and validating data from large or complex
datasets.
● Experience developing reports, dashboards, analyses, or automated processes using
data.
● Familiarity with data visualization and business intelligence tools such as Tableau,
Power BI, or similar platforms.
● Strong analytical and problem-solving skills, with the ability to identify trends,
inconsistencies, and meaningful insights.
● Ability to clearly document analytical procedures, findings, assumptions, and
conclusions.
● Strong written and verbal communication skills, with the ability to explain technical
concepts to non-technical stakeholders.
● Demonstrated ability to manage priorities, meet deadlines, ask thoughtful questions, and
work effectively in a collaborative environment.
● Willingness to learn new tools, technologies, business processes, and audit
methodologies.

Nice to haves:
● Bachelor’s degree in Data Science, Computer Science, Information Systems,
Mathematics, Statistics, Business, Accounting, Finance, or a related field.
● Experience supporting Internal Audit, Risk, Compliance, Finance, or other control-related
functions.
● Experience applying data analytics to audit planning, risk assessments, audit testing, or
continuous monitoring.
● Experience building dashboards or visualizations in Tableau, Power BI, or similar tools.
● Exposure to data transformation workflows using dbt or similar technologies.
● Familiarity with Git, GitHub, code version control, peer reviews, or software development
best practices.
● Exposure to financial services, banking, lending, payments, investing, or other regulated
industries.
● Progress toward or interest in professional certifications such as CIA, CISA, CPA,
CRMA, CAMS, or data analytics-related certifications.
● Exposure to advanced analytics, machine learning, predictive modeling, or AI-enabled
audit techniques.