Quantitative Investment Analyst

Magnetar•Evanston, IL

8d•$125,000 - $200,000

About The Position

Magnetar's Quantitative Investing team is seeking a driven, intellectually curious Quantitative Investment Analyst to join our team. This individual will collaborate closely with portfolio managers and researchers to research, develop, and refine systematic investing strategies across the full landscape — including but not limited to convertible, statistical, risk, and volatility arbitrage. The ideal candidate is a highly motivated self-starter with a genuine passion for finance and investing, who thrives in a fast-paced, intellectually demanding environment.

Requirements

Bachelor's or advanced degree in Mathematics, Statistics, Engineering, Computer Science, Finance, Economics, or a related quantitative field
3–5 years of direct, hands-on experience at a hedge fund or institutional buy-side or sell-side firm, with meaningful exposure to a quantitative strategy desk — such as Risk Arbitrage, Convertible Bond Arbitrage, Volatility Arbitrage, Statistical Arbitrage, or a comparable quantitative strategy
Demonstrable first-hand knowledge of Risk Arbitrage with the ability to independently initiate and carry out research and back up the Risk Arb desk
Working knowledge of, and the ability to conduct research across, the broader arbitrage landscape — convertible, statistical, and volatility arbitrage in particular
Strong quantitative and analytical skills; proficiency in Python, R, MATLAB, or similar programming languages, with hands-on experience in statistical modeling, time-series analysis, or machine learning
Solid understanding of financial concepts including portfolio theory, risk/return frameworks, financial instruments, and market dynamics across asset classes
Financial acumen and demonstrated curiosity about investing — someone who reads financial news, thinks critically about market dynamics, and is genuinely passionate about all things finance
Highly driven, proactive self-starter who takes initiative, operates with urgency, and thrives in an environment that rewards intellectual curiosity and independent thinking
Excellent communication skills with the ability to translate complex quantitative analysis into clear, actionable insights for both technical and non-technical audiences
Familiarity with applied AI/ML techniques in a financial context, including experience fine-tuning large language models (LLMs) and developing agentic workflows to automate research, data extraction, or investment processes

Responsibilities

Research, develop, and back-test quantitative arbitrage strategies — including convertible, statistical, volatility, and related approaches — across equities, fixed income, credit, and other asset classes
Support, and where needed serve as a back-up for, the Risk Arbitrage desk — independently initiating research while carrying out assigned tasks/analysis
Analyze large datasets to identify and validate alpha signals, risk factors, and portfolio construction insights using statistical and machine learning techniques
Partner with portfolio managers to translate research findings into actionable investment insights and implement strategies within the portfolio
Monitor and evaluate the ongoing performance of quantitative models, identifying degradation and proposing enhancements as market conditions evolve
Stay current on developments in quantitative finance, market microstructure, and macroeconomic trends, proactively sharing insights with the team
Collaborate cross-functionally with technology, risk management, and operations teams to support the full investment lifecycle
Design and deploy AI-powered tools and agentic workflows — including fine-tuned LLMs — to enhance research automation, alternative data processing, and investment decision support