Senior Manager, Securities Lending Quant

Charles Schwab Inc.•Westlake, TX

6d•$105,600 - $200,000

About The Position

As a Senior Manager, Securities Lending Quant, you will serve as a senior desk-facing quantitative expert within the Treasury Modeling department, focused on securities lending, prime brokerage, margin lending, and equity finance. This role is designed for someone who understands how securities lending desks operate, can speak the language of traders, and can turn market structure, inventory, client demand, collateral, pricing, and P&L dynamics into practical analytics that improve decision-making. The ideal candidate brings deep prime brokerage or securities lending expertise, strong quantitative instincts, and a commercial mindset. You should be able to identify trader pain points, challenge existing processes, bring forward innovative quant ideas, and implement solutions that are useful, explainable, and adopted by the business. This is a high-impact individual contributor role, not a formal people-leadership position. You will influence through product expertise, desk judgment, quantitative creativity, and the ability to partner closely with Treasury, Finance, Model Risk Management, product teams, and desk stakeholders. Success in this role requires someone who can bridge desk intuition and analytical rigor while delivering tools and insights that change how the business operates. If you are a securities lending quant with a strong prime brokerage foundation, a feel for desk economics, and the vision to build next-generation analytics for trading and balance sheet decisions, we encourage you to apply.

Requirements

Bachelor’s degree in a quantitative field, finance, economics, engineering, physics, mathematics, statistics, computer science, or equivalent experience.
8+ years of experience in financial services as a securities lending quant, desk strategist, prime brokerage quant, quantitative strategist, or similar role supporting financing, risk, pricing, inventory, or P&L decisions.
Deep understanding of prime brokerage, securities lending, collateralized lending, margin, financing spreads, balance sheet usage, client behavior, and secured product economics.
Strong knowledge of equity-linked products, including how equity markets, derivatives, hedging activity, client flows, and financing dynamics affect balances, valuation, pricing, and P&L.
Ability to translate trader needs and ambiguous business questions into practical quantitative tools, decision frameworks, and implementation plans that improve desk outcomes.
Strong Python or similar programming experience, with the ability to work efficiently with large datasets and controlled production environments.
Strong communication skills, including the ability to engage credibly with traders and explain quantitative insights to both technical and non-technical stakeholders.
Experience operating in a governed model environment, including documentation, validation support, monitoring, and controlled change management.

Nice To Haves

Graduate degree, such as an M.S. or Ph.D., in a quantitative discipline.
Direct experience on or closely supporting a securities lending desk, prime brokerage desk, equity finance desk, margin lending function, or related desk-facing business.
Strong understanding of securities lending and borrowing, rebate rates, fees, utilization, specials, collateral, financing spreads, short demand, and desk-level P&L drivers.
Demonstrated ability to identify desk pain points and build practical analytics for inventory management, release-engine decisions, client demand, pricing, valuation, utilization, margin balances, or P&L explainability.
Experience with broker-dealer Treasury, balance sheet management, funding, liquidity, capital, or transfer pricing concepts.
Familiarity with model risk management expectations, including validation, performance monitoring, limitation documentation, and production governance.
Experience building analytics that support securities lending release-engine decisions, including inventory availability, borrow demand, collateral usage, margin balance behavior, rate/fee dynamics, and production decision routines.
Hands-on experience operationalizing product analytics for securities lending businesses, including controlled production runs, exception management, transparent outputs, and monitoring of key release-engine drivers.
Vision for where advanced analytics, AI/ML, automation, or alternative quantitative methods can create measurable trading, financing, client, or balance sheet value while remaining explainable and governable.

Responsibilities

Develop desk-facing quantitative analytics for securities lending, margin lending, and prime brokerage, with a focus on inventory, release decisions, pricing, demand signals, utilization, risk, and P&L drivers.
Partner with traders and desk stakeholders to understand pain points, pressure-test assumptions, and convert complex business questions into actionable quant solutions.
Analyze how client activity, market conditions, collateral dynamics, financing spreads, utilization, and product mechanics flow through balances, revenues, valuation, and P&L outcomes.
Enhance securities lending release-engine analytics by connecting inventory availability, borrow demand, margin balances, collateral, pricing, client activity, and desk-level P&L into clear decision frameworks.
Design analytics that strengthen securities inventory management, including availability, utilization, demand signals, collateral dynamics, concentration risk, and balance sheet optimization.
Partner closely with Treasury, Finance, Model Risk Management, product teams, and desk stakeholders to ensure models reflect real product behavior, market structure, and business economics.
Produce clear technical documentation, white papers, model methodology notes, monitoring materials, and stakeholder-ready explanations of model results.
Support model governance activities, including validation, limitation assessment, performance monitoring, change management, and ongoing model maintenance.
Identify opportunities to improve analytical accuracy, automation, controls, and business adoption across securities lending and related products.
Bring forward and pilot innovative quantitative, AI/ML, automation, or statistical approaches that can improve trading decisions, inventory deployment, pricing, risk measurement, or P&L explainability.
Serve as a senior securities lending thought partner who shapes analytical direction through domain depth, desk intuition, credibility with stakeholders, and strong execution.