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    Goldman Sachs

    Financial Services

    GBM - Quantitative Dev/Strat - Systematic Rates Trading, New York

    New York, United StatesOn-SitePart-time$150k – $225k / yearPosted 3w ago
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    Job description

    Quant Dev/Strat - Systematic Rates Trading

    Desk Overview

    The Systematic Rates Trading desk sits at the intersection of quantitative research, technology, and market-making execution. The team is responsible for overseeing the systematic trading, pricing, and risk management frameworks for global Rates products (including government bonds, interest rate swaps, and futures). We design, build, and manage real-time pricing engines, algorithmic hedging systems, and execution platforms that operate at scale in highly liquid and volatile markets.

    Role Description

    This is a high-impact, front-office seat designed for a strong Quantitative Developer / Strat who is a self-driven, highly motivated independent thinker. In this role, you will not just implement pre-defined models; you will actively drive the end-to-end development of trading algorithms, market-making logic, and portfolio optimization tools.

    We are looking for an individual who takes a high amount of ownership over their work, from initial exploratory data analysis to production-grade deployment. You will collaborate closely with traders and quantitative researchers to optimize execution, analyze market microstructure, and build robust, high-performance systems where code quality directly impacts desk P&L.

    Responsibilities

    • Algorithm Development: Design, develop, and optimize systematic trading algorithms, market-making logic, and real-time algorithmic hedging systems.
    • Exploratory Data Analysis (EDA): Conduct rigorous data analysis on massive, high-frequency market datasets to identify pricing anomalies, refine trading signals, and improve execution strategies.
    • Market Microstructure & TCA: Analyze Rates market microstructure and build sophisticated Transaction Cost Analysis (TCA) frameworks to minimize slippage, model market impact, and optimize execution performance.
    • Portfolio Optimization: Implement and refine mathematical models for portfolio optimization, risk allocation, and real-time risk management.
    • System Architecture & Performance: Design and maintain the high-performance, low-latency trading infrastructure and data pipelines powering the systematic Rates business.
    • End-to-End Ownership: Proactively identify technical bottlenecks, propose architectural improvements, and take full responsibility for the reliability and scalability of the trading stack.

    Who We Look For

    We are seeking an exceptional software engineer and quantitative thinker with a "builder" mindset. You should thrive in a fast-paced, collaborative trading floor environment where you are expected to work independently, think critically, and take complete ownership of your projects.

    Basic Qualifications

    • Education: Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, Financial Engineering, Mathematics, or a related quantitative field.
    • Core Languages: Expert-level proficiency in C++ or Java (for high-performance, low-latency systems) and Python (for data analysis, prototyping, and scripting).
    • CS Fundamentals: Strong foundation in data structures, algorithms, systems programming, and concurrent/multi-threaded application design.
    • Engineering Best Practices: Deep understanding of the software development lifecycle, including version control (Git), CI/CD pipelines, testing frameworks, and performance profiling.
    • Problem Solving: Exceptional debugging skills and the ability to navigate complex, distributed systems under time-sensitive, live-trading conditions.

    Preferred Qualifications

    • Domain Knowledge: Strong understanding of Rates products (Treasuries, Swaps, Futures), yield curve modeling, and fixed-income analytics.
    • Industry Experience: Prior experience working as a Quant Developer, Strat, or Software Engineer on a systematic trading desk, market-making team, or high-frequency trading (HFT) firm.
    • Data Engineering: Experience building and maintaining large-scale time-series databases (e.g., KDB+/q, SQL) and ETL pipelines.
    • Quantitative Skills: Familiarity with statistical modeling, optimization techniques, and machine learning libraries in Python.

    Salary Range
    The expected base salary for this New York, NY, United States-based position is $150000-$225000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year-end.

    Benefits
    Goldman Sachs is committed to providing our people with valuable and competitive benefits and wellness offerings, as it is a core part of providing a strong overall employee experience. A summary of these offerings, which are generally available to active, non-temporary, full-time and part-time US employees who work at least 20 hours per week, can be found here.

    Job details are sourced from the employer's original posting.

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    About the company

    Goldman Sachs

    Our team of engineers builds solutions to the most complex problems. We develop cutting-edge systems and processes that form the core of our key business and enable transactions to move in milliseconds. We provide real-time access to critical deal information and crunch billions of data points each day to inform firm-wide market insights and strategies. Team members have the opportunity to work at the forefront of technology innovation alongside industry leaders and make significant contributions to the field.

    View all Goldman Sachs jobs
    Industry
    Financial Services
    Founded
    1869
    Open roles
    1195

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