Systematic Quantitative Analyst

Citi; New York (NY); On-site; USD 247,500 - 302,500; Full time

Job summary

Citi in New York seeks a quantitative analyst to design and implement live pricing and trade execution algorithms for fixed‑income instruments. You will develop yield curves, back‑test models, and build predictors for pricing, volatility, and risk.

Collaboration with traders and technologists is essential, leveraging a wide range of programming languages and math tools. The role requires a master’s level background in OR/Financial Engineering or an equivalent with substantial practical

Qualifications

• Requires an advanced degree in OR/Financial Engineering or equivalent with 5 years of real‑time pricing/trading algorithm experience.
• Experience calibrating and assessing ML predictors; maintaining pricing/hedging infrastructure; and building data-science libraries.
• Proficiency in Python, kdb, SQL, mathematical finance, and Monte Carlo methods; knowledge of PDE solvers.

Responsibilities

• Build live pricing and trade execution algorithms for fixed income.
• Develop automated quantitative strategies for pricing and quoting.
• Create yield curves for pricing bonds, swaps, FRAs, and other instruments.
• Back-test, simulate, and report model performance; calibrate predictors.
• Develop pricing, hedging, and risk analytics libraries and infrastructure.
• Collaborate with traders, structurers, and tech professionals.

Skills

Python

C++

C#

Java

Mathematical finance

Statistics

Machine learning

Education

Master’s degree in Operations Research or Financial Engineering

Bachelor’s degree + 7 years relevant experience

Tools

kdb

SQL

STL (C++)

Job description

Responsibilities

• Build algorithms for the live pricing of fixed income instruments.
• Build trade execution algorithms.
• Develop automated and semi‑automated quantitative strategies used by trading professionals to price and quote fixed‑income instruments for clients.
• Build, configure and use yield curves to price fixed‑income instruments such as bonds, swaps, futures, and forward rate agreements (FRAs).
• Assess the performance of the above models by running back‑tests and simulations, and create reports to monitor ongoing performance.
• Research, implement and maintain predictors for various financial quantities involved in trading (prices, volumes, volatility, bid‑ask spreads).
• Calibrate and assess the quality of in‑house built and third‑party statistical and machine‑learning predictors.
• Develop success metrics for predictors and implement reports for monitoring their performance.
• Build and implement models and algorithms to hedge portfolios of fixed‑income instruments and to analyze risk.
• Develop and maintain infrastructure for researching and executing pricing, hedging and prediction algorithms.
• Specify algorithmic pricing and trading infrastructure needs.
• Rationalize and clean‑up existing codebases for algorithmic trading and pricing.
• Develop quantitative analytics libraries used for pricing and risk‑management.
• Create, implement, and support quantitative models for the trading business leveraging a wide variety of mathematical and computer science methods and tools including hardware acceleration, advanced calculus, C++ (including STL), C#, .NET, Java, object‑oriented software design, Python, kdb, Structured Query Language (SQL), mathematical finance/programming and statistics and probability.
• Develop quantitative pricing models using numerical techniques for valuation, including Monte Carlo Methods and partial differential equation solvers.
• Collaborate closely with Traders, Structurers, and technology professionals.

Qualifications

• Requires a Master’s degree, or foreign equivalent, in Operations Research, Financial Engineering or a related field and 5 years of experience as a Quantitative Analyst, Quantitative Trading Analyst, or related position developing real‑time pricing and trade execution algorithms for fixed‑income instruments at a financial services institution.
• Alternatively, requires a Bachelor’s degree in the stated fields and 7 years of progressively responsible, post‑baccalaureate experience.
• Full span of experience must include: calibrating and assessing statistical and machine‑learning predictors; maintaining infrastructure for pricing, hedging and prediction algorithms; developing core analytical capabilities and data‑science/machine‑learning libraries; hardware acceleration, advanced calculus, performance‑oriented programming languages, object‑oriented software design, Python, kdb, SQL, mathematical finance/programming, and statistics/probability concepts including Monte Carlo Methods and partial differential equation solvers; developing yield curves to price fixed‑income instruments; and algorithmic market making including market microstructure.

Wage Range: $275,000 to $275,000.

Location: New York, New York, United States.

In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.

Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

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