Quantitative Analytics Engineer

About the role

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.

Responsibilities

• Lead data science projects focused on Schwab’s margin and trading data.
• Evaluate client and market data to detect risk patterns using modeling and analysis techniques.
• Convert detected risk patterns into functional models that help dictate and challenge how that risk is managed.
• 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.

Qualifications

• Knowledge of brokerage business processes and regulatory requirements.
• Exposure to other cloud platforms (AWS, Azure, GCP) and hybrid cloud architectures.
• Experience with automation and DevOps platforms.
• Experience with C# or Java service-based architectures.
• Experience with data science and implementing machine learning.