Senior Manager, Risk Analytics and Modeling

Charles Schwab Corporation; Southlake (TX); Hybrid; USD 130,000 - 180,000; Full time

Job summary

Charles Schwab Corporation is seeking a Senior Manager in Model Risk Oversight focused on model validation and related initiatives. The role emphasizes fraud and AML models, with potential for junior responsibilities for less experienced candidates.

Responsibilities include validation per SR 26-2, reporting to model owners and senior management, collaboration with internal analysts and external consultants, and annual reviews of model performance and governance.

Qualifications

• 2+ years of experience in fraud monitoring and anti-money laundering.
• 5+ years of quantitative experience.
• Advanced degree in statistics, mathematics, physics, engineering, economics, or a related quantitative field.
• Knowledge of model governance and U.S. banking regulations.
• Proficiency in Python, SAS, R, or other statistical programming languages.

Responsibilities

• Validate models in accordance with SR 26-2, including model use, documentation, conceptual soundness, data integrity, controls, and software.
• Prepare model validation reports and present findings to model owners and senior management.
• Partner with internal analysts and external consultants on validation activities.
• Evaluate model performance monitoring and complete annual model reviews.

Skills

Fraud monitoring

Quantitative analysis

Python/SAS/R

Model governance

US banking regulations

Communication skills

Education

Advanced degree in quantitative field

PhD in data science / quantitative field

Job description

Your Opportunity

At Schwab, you’re empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us “challenge the status quo” and transform the finance industry together. Please note: This position is M-F during standard business hours with a hybrid work model (4 days in-office, 1 day working from home). It is only available in the areas listed. Candidate must reside or be willing to relocate on their own to one of the listed areas. Applicants must be currently authorized to work in the United States on a full-time basis without employer sponsorship.

Model Risk Oversight is a strategic function within Corporate Risk Management that uses advanced quantitative methods and a broad range of models to support innovative client solutions and manage financial and reputational risk. The team identifies, reviews, and monitors models used across the organization.

We are seeking candidates for a Senior Manager individual contributor role focused on model validation and broader Model Risk Oversight initiatives. Candidates should have strong quantitative skills and business experience with fraud and anti-money laundering models. Less experienced candidates may be considered for junior roles.

Job responsibilities include:

• Validate models in accordance with SR 26-2, including model use, documentation, conceptual soundness, data integrity, controls, and software.

• Prepare model validation reports and present findings to model owners and senior management.

• Partner with internal analysts and external consultants on validation activities.

• Evaluate model performance monitoring and complete annual model reviews.

What you have

Required Skills and Qualifications:

• 2+ years of experience in fraud monitoring and anti-money laundering.

• 5+ years of quantitative experience.

• Advanced degree in statistics, mathematics, physics, engineering, economics, or a related quantitative field.

• Knowledge of model governance and U.S. banking regulations.

• Proficiency in Python, SAS, R, or other statistical programming languages.

Preferred Skills and Qualifications:

• Ph.D. in quantitative fields, such as data science, statistics, mathematics, physics, or engineering.

• Experience developing and applying machine learning models.

• 5+ years of model validation experience.

• 2+ years of experience with digital assets.

• Experience working with large, unstructured data sets.

• Knowledge of digital asset regulations, fraud, and AML.

• CFA, FRM, ACAMS, or digital asset certifications.

• Quantitative finance experience.

• Strong verbal and written communication skills.

• Strong interpersonal skills.

• Excellent relationship-building skills.