Staff Internal Auditor, Data Analyst

The role:

SoFi is seeking a Staff Internal Auditor, Data Analytics lead to join the SoFi Internal Audit (IA) Department, reporting to Senior Manager, Data Analytics, Internal Audit.  You will be helping to build the foundation for IA’s data analytics function, supporting engagement teams in various audits, and assisting in special projects, as necessary.  This is a hands-on, creative role on a growing team with a vast opportunity to further expand the functions capabilities, efficiency, and effectiveness.

What you’ll do: 

• Identify, design, implement, and maintain the data analytics routines needed to support audit activities performed including both audit execution, continuous auditing, and department level audit operations and reporting. 
• Proactively establish connections with key data owners and help IA build and understand metadata to support the analytics being performed.
• Assist with the establishment and maintenance of an IA Team Datamart to store and manage confidential IA data for audit testing and routine reporting.
• Develop and maintain a successful system of data analytics which will provide enhanced understanding into risks and controls and establish an efficient/automated means to analyze and increase testing volumes of data for outliers, anomalies, patterns, and trends to evaluate the design and effectiveness of controls.
• Enhance the use of data analytics within the Department and drive data strategy and efficiency.
• Interact with the IA Leadership Team and business/functional area management to identify appropriate data sources and data elements required for analytics.
• Identify, design, and develop data analytics extract techniques to support the audit activities performed by IA.
• Implement and manage the infrastructure required to support data extraction, storage, transformation, and processing through data analytics techniques and generating output for visualization/analysis by IA.
• Automate audit testing and develop techniques for continuous auditing and the ability to analyze large volumes of data.
• Define how automation and continuous auditing fits into our overall Departmental workflow – risk assessment, testing, and reporting.
• Create automation and continuous auditing dashboards for monitoring.
• Produce regularly scheduled or ad-hoc reports to communicate the progress and assess the effectiveness of the IA program. Assist with quarterly Board reporting as required.
• Represent IA, as directed, on committees and/or special project teams as necessary.

What you’ll need:

• Minimum 2+ years of relevant audit work experience, with at least two years of data analysis and/or statistical modeling analysis.
• Strong experience with analytics tools including but not limited to Excel, SQL, Alteryx, Python, R, etc.
• Strong experience with data visualization tools such as Tableau. 
• Knowledge of internal and/or external auditing standards.
• Proficient understanding and application of data analysis used in either financial services, audit, and/or risk management functions.
• Demonstrated quantitative, analytical, data-intuition, problem-solving skills, and proficiency in data analytics and automation techniques.
• Experience with utilizing data over annual audit planning, risk assessments and continuous auditing is preferred.

Nice to have:

• A bachelor’s degree or equivalent in relevant fields of study - Data Science, Computer Science, Information Systems, Mathematics, Statistics, Business, or another related field is desirable.
• Professional certifications attained or in progress related to auditing, risk management, and/or data sciences is desirable.
• A basic background in Data Engineering with experience using Apache Airflow or similar platforms to schedule, automate, and monitor data pipelines for continuous monitoring.
• Hands-on experience with platforms such as Snowflake, BigQuery, Redshift, or Data Bricks to optimize SQL queries for large datasets, and handle semi-structured data.
• Knowledge of data transformation workflows, ideally DBT (Data Build Tool) to build documents, and test data models.
• Proficiency using Git/GitHub for code management, peer reviews, and maintaining a history of changes to audit scripts.