Senior Specialist, Internal Audit, Risk Analytics/Modeling

Your opportunity

The Internal Audit Department (IAD) of The Charles Schwab Corporation provides independent and objective assessments to figure out whether all significant risks are identified and appropriately reported by management and risk functions to the Board and Executive Management, to evaluate whether risks are adequately controlled, and to challenge Executive Management to improve the efficiency of governance processes, risk management, and internal controls.

The Technology Internal Audit team is seeking a Senior Specialist, Internal Audit, Risk Analytics/Modeling and Technology Audit. The Technology audit team is responsible for the execution of audits over the firm’s risk management functions, including model risk as well as technology infrastructure audits.  We are hiring a specialist who has preferably experience performing model risk audits (model development, governance and validation controls) and knowledge of technology infrastructure concepts in order to support testing of information technology controls.

The candidate will need a good understanding of statistics, models, and technology infrastructure and controls. The role includes performing testing as part of audit reviews of various model types including those that support financial services process such as: Capital Stress Testing (CST), Fraud, Anti-Money Laundering (AML), Credit risk, Interest Rate risk, Margin risk, Investment risk, Business Intelligence/Marketing, and Cybersecurity. Testing of technology infrastructure includes platforms (Operating Systems, Databases, Network, etc.) and general technology controls (Change Management, User Provisioning, Batch Processing, Problem/Incident Management, etc.)

What you’ll do:

• Audit Execution (Models):
• Assist with performing audit reviews of model development and validations following guidelines based on SR 26-2 Guidance on Model Risk Management, to include an assessment of model usage, documentation, conceptual soundness, annual reviews, and performance monitoring
• Document audit work performed using defined model audit templates, reports, as well as through leading meetings and discussions that support testing activities with model owners, validators, and Internal Audit leaders.
• Work effectively as a team member with other Internal Audit team members and with other quantitative analysts at the company.
• Participate in the execution of internal audit assignments on models, ensuring work is performed in accordance with IAD methodology.
• Audit Execution (Technology Infrastructure):
• Participate in the planning and execution of internal audit assignments specific to technology. Ensure work is performed in accordance with IAD methodology. Responsibilities will include scheduling and participation in audit meetings; participation in prioritization discussions; drafting of audit work; design and execution of testing; and completion and review of work papers. Additionally, assist in the tracking of team operations including audit status, issue status, and budgets.
• Issues Identification: Based on the results of audit testing, identify and draft audit observations for review by the Internal Audit Manager/Senior Manager (and above levels) and subsequent debriefing with the key partners (typically VP-level and below).
• Issue Management and Validation: Conduct validation testing of the audit issue action plans completed by the business.
• Coaching: Provide support, mentoring, and feedback to audit team members throughout the audit. Provide assistance with onboarding and ongoing support to new team members.
• Administration/Training: Completion of firm-wide and departmental administration and training requirements.
• Other Initiatives/Special Projects: As needed, assist with special projects related to business operational improvement or internal team needs.

What you have

• Preferred experience performing internal audits amongst a complex operational and regulatory environment.
• Ability to work as a member of a project team and cultivate a strong working relationship with external co-sourcing providers and internal lines of businesses.
• Working on or attained advanced degree in a quantitative field (data science, economics, statistics, finance, mathematics, computer science, physics)
• Strong oral and written communication skills
• Excellent people skills
• Understanding of statistical concepts, predictive modeling fields, and analytical tools, such as SAS, R, Python, or MATLAB 
• Exposure to model governance processes and regulatory requirements for large US banks