Manager, Risk Analytics/Modeling

Charles Schwab Corporation; Saskatchewan; Hybrid; CAD 80,000 - 100,000; Full time

Job summary

A leading financial services firm is seeking a quantitative analyst to assess model risks and validate financial models. The role involves utilizing advanced statistical tools and machine learning techniques to ensure accuracy and performance of models. Candidates should have a Master's degree in a relevant field and experience with AI applications in finance. Competitive pay and a hybrid work schedule are offered.

Benefits

401(k) with company match

Employee stock purchase plan

Paid vacation

28-day sabbatical after 5 years

Paid parental leave

Tuition reimbursement

Health, dental, and vision insurance

Qualifications

• Master's degree required in relevant fields.
• Experience with machine learning and AI models.

Responsibilities

• Evaluate model risk using statistical and analytical tools.
• Perform model validations and sensitivity testing.
• Present findings in formal reports to senior management.

Skills

Statistical Analysis

Analytical Tools

Machine Learning

Python

Education

Master's degree in Statistics

Master's degree in Mathematics

Master's degree in Financial Engineering

Tools

SAS

R

MATLAB

Python

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.

Duties:

• Utilize a broad spectrum of statistical and analytical tools to evaluate model risk at the company.
• Prudently manage financial risk using sophisticated quantitative approaches.
• Perform model validations following guidelines based on SR 11-7, including assessment of model usage, documentation, conceptual soundness, data integrity, control environment, and software environment.
• Assess the rationale and supporting evidence for model choices.
• Identify and assess model assumptions and limitations, and evaluate model accuracy and performance.
• Independently replicate models from theory to ensure accurate implementation and develop “toy” benchmark models to assess model performance and uncertainty.
• Perform sensitivity testing, back testing, and other statistical and econometric analyses.
• Present work through formal model validation reports and verbal presentations to model owners and senior management.

What you have

Job Responsibilities:Master's degree in Statistics, Mathematics, Financial Engineering, Management Information Systems, Information Management, or related field. Completion of graduate-level coursework, research projects, or internships involving:

• SAS, R, MATLAB, or Python;
• Utilizing machine learning models such as Gradient Descent Regressors and Classifiers, clustering algorithms, and reinforcement learning models like multi-armed bandits;
• Artificial intelligence (AI) and Generative AI models;
• Applying machine learning and AI to financial investment and advisory models;
• Validations of Monte Carlo and modern portfolio construction methods used in advanced advisory models and active equity approaches.

We offer competitive pay and benefits. Starting compensation depends on related experience. Annual bonus and other earnings are not included in the ranges above. Benefits include: 401(k) with company match, employee stock purchase plan, paid vacation, volunteering, a 28-day sabbatical after every 5 years of service for eligible positions, paid parental leave and family benefits, tuition reimbursement, health, dental, and vision insurance, and a hybrid/remote work schedule for eligible positions (subject to Schwab’s internal workplace flexibility policies).