Quantitative Trading Assistant

Institutional Equity Division – Salt Lake City

About the Division

The Institutional Equity Division (IED) is a global leader in the origination, distribution, and trading of equity, equity-linked, and equity-derivative securities. Our Sales & Trading teams provide liquidity, deliver market insights, and design innovative solutions to help clients achieve superior performance.

Role Overview

We are seeking a Quantitative Trading Assistant to support front-office equity derivatives trading. This role is critical in ensuring the accuracy and robustness of our pricing and risk models in real time. You will work closely with traders and strategists to maintain market parameters, troubleshoot issues, and optimize workflows in a fast-paced environment.

Key Responsibilities

Oversee real-time model calibration and market parameter maintenance.

Monitor market data (volatility surfaces, dividends, borrow curves, yield curves) and resolve fit errors promptly.

Troubleshoot exchange-related quote issues and ensure smooth trading operations.

Validate new-name fits and manage corporate actions and basket compositions.

Collaborate with traders, strats, and support teams to address live requests quickly and accurately.

What We’re Looking For

Exceptional attention to detail and ability to work under pressure.

Strong technical aptitude with experience in model calibration frameworks and script-driven workflows.

Critical thinking skills to diagnose, escalate, and resolve complex issues.

Excellent communication and collaboration skills across multiple teams.

Familiarity with equity derivatives concepts (vol surfaces, dividends, borrow curves, forward pricing, yield curves).

Prior experience in a front-office or quant-adjacent support role within equities or derivatives.

Exposure to structured products, equity derivatives, or options market-making environments.

Preferred Technical Background

Mathematics: Linear algebra, multivariate regression, optimization techniques, PDEs, stochastic processes.

Quantitative Finance: Option pricing (PDE, Monte Carlo), risk-neutral measures, volatility modeling.

Programming: Proficiency in Python