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About the Role

The Corporate Risk Management team provides an integrated risk management strategy to support predictable financial and operational performance and successful client and shareholder outcomes. This role on the Margin Risk & Data Solutions team will lead data science projects focused on margin and trading data, evaluating client and market data to detect risk patterns using modeling and analysis techniques. Responsibilities include converting insights into functional models, model documentation, development evidence, and performance monitoring for production models. Strong experience analyzing, manipulating, and visualizing large datasets is essential. This is an Individual Contributor role.

Responsibilities

Design, improve, and deploy equity option and exposure models for financial risk analytics, focusing on margin and trading data.
Lead the management and maintenance of retail trading data sets.
Collaborate with internal developers and architects to connect models with core banking platforms and workflows.
Document model development, deployment processes, and integration steps for internal and external review.
Analyze large datasets, identify risk patterns, and translate insights into actionable models.
Present technical approaches and results to management, auditors, and business partners.
Contribute to an Agile team, iterating quickly and delivering impactful solutions.

Requirements

Bachelor's or Master's degree in Computer Science, Mathematics, Engineering, Data Science, Finance or related field.
5+ years of experience in model development, preferably in financial services.
5+ years of experience with SQL, data manipulation, and data visualization.
Strong Python skills; experience with data analysis and manipulation frameworks (Pandas, NumPy, PySpark, etc).
Strong fundamentals in option models and retail derivatives trading.
Experience with option and equity trading models and brokerage margin policies, particularly Black-Scholes, binomial option models, value-at-risk techniques, futures SPAN margin, Monte Carlo methods, and regression.
Ability to manage multiple deliverables and drive process improvements.
Excellent communication skills and documentation abilities.

Skills

SQL
Data manipulation
Data visualization
Python
Pandas
NumPy
PySpark
Option models
Retail derivatives trading
Option trading models
Equity trading models
Brokerage margin policies
Black-Scholes
Binomial option models
Value-at-risk techniques
Futures SPAN margin
Monte Carlo methods
Regression
Agile methodologies
AWS
Azure
GCP
Automation
DevOps
C#
Java
Machine learning

Location

Omaha
Chicago
Austin
Southlake
Westlake

Work Type

Hybrid

Experience Level

5+ years of experience in model development
5+ years of experience with SQL, data manipulation, and data visualization

Education Level

Bachelor's or Master's degree in Computer Science, Mathematics, Engineering, Data Science, Finance or related field.

About the Company

The mission of Corporate Risk Management is to provide an integrated risk management strategy that supports the delivery of predictable financial and operational performance and produces successful client and shareholder outcomes. Corporate Risk Management serves as Schwab’s second line of defense by providing independent assessments of the firm’s risk, using models, controls, and systems to measure financial, operational, compliance, and legal risks to Schwab’s business, employees, and customers.