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Temporary Algorithmic Trader information

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$39.5K

$96.8K

$269.5K

How much do temporary algorithmic trader jobs pay per year?

As of Jul 11, 2026, the average yearly pay for temporary algorithmic trader in the United States is $96,774.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,500.00 and $105,500.00 per year, depending on experience, location, and employer.

Is algo trading 100% profitable?

Algorithmic trading as a profession involves developing and implementing trading strategies that can be profitable, but it is not guaranteed to be 100% profitable. Market conditions, strategy quality, and risk management significantly influence outcomes, and losses are possible. Successful algo traders continuously refine their models and use tools like backtesting and real-time monitoring to improve performance.

What is the difference between Temporary Algorithmic Trader vs Quantitative Analyst?

AspectTemporary Algorithmic TraderQuantitative Analyst
Required CredentialsDegree in finance, computer science, or related field; programming skills; trading certificationsDegree in finance, mathematics, or statistics; programming skills; advanced degrees often preferred
Work EnvironmentTrading floors, financial firms, hedge funds; fast-paced, deadline-drivenResearch labs, financial institutions; analytical, data-driven
Employer & Industry UsageFinancial trading firms, hedge funds, investment banksAsset management firms, investment banks, financial consultancies

While both roles require strong quantitative skills and programming knowledge, a Temporary Algorithmic Trader focuses on executing trading strategies in real-time markets, often in a fast-paced environment. A Quantitative Analyst typically develops models and conducts research to inform trading decisions, often working in a more analytical setting. The temporary nature of the Algorithmic Trader role emphasizes short-term trading activities, whereas Quantitative Analysts may have ongoing research responsibilities.

Can ChatGPT write a trading algorithm?

A Temporary Algorithmic Trader can use ChatGPT to generate code snippets or ideas for trading algorithms, but it cannot independently develop fully functional, optimized trading systems. Developing effective algorithms requires expertise in programming, financial markets, and backtesting tools. ChatGPT can assist with coding guidance but should be complemented by thorough testing and domain knowledge.

What are Temporary Algorithmic Traders?

Temporary Algorithmic Traders are professionals hired on a short-term basis to develop, implement, or manage algorithmic trading strategies for financial markets. Their work involves using mathematical models and computer programs to automate trading decisions, aiming to optimize profits and manage risk. These traders may be brought in for specific projects, to cover staff shortages, or to contribute expertise in algorithm development and data analysis. Temporary positions can range from a few weeks to several months, depending on the organization’s needs. They often work for banks, hedge funds, or proprietary trading firms.

How much does an algorithmic trader make?

Algorithmic traders typically earn between $70,000 and $150,000 annually, with experienced professionals and those working at hedge funds or proprietary trading firms earning higher salaries and bonuses. Compensation often depends on skills in programming, quantitative analysis, and trading strategies, as well as performance and firm size.

How does a temporary algorithmic trader typically collaborate with permanent team members and adapt to established trading strategies?

As a temporary algorithmic trader, you’ll often work closely with permanent trading teams to quickly understand and integrate into their existing strategies and workflows. Effective communication is essential, as you may need to adapt your coding style, share insights, and receive feedback from more experienced colleagues. Temporary traders are expected to ramp up swiftly, contribute to ongoing projects, and ensure their algorithms align with risk management protocols and performance goals. This collaborative environment enables you to learn from seasoned professionals while making meaningful contributions, even within a limited timeframe.

What are the key skills and qualifications needed to thrive as a Temporary Algorithmic Trader, and why are they important?

To thrive as a Temporary Algorithmic Trader, you need strong quantitative analysis skills, proficiency in programming (such as Python or C++), and a solid understanding of financial markets, often backed by a degree in finance, mathematics, or computer science. Familiarity with trading platforms, statistical analysis tools, and backtesting software like MATLAB or R is typically required. Critical thinking, attention to detail, and the ability to work under pressure are important soft skills that help traders excel in fast-moving environments. These skills and qualities are crucial for developing, implementing, and refining trading strategies that can adapt to dynamic market conditions.

Is algorithmic trading illegal?

Algorithmic trading is legal in most jurisdictions when conducted within regulatory frameworks that require proper registration, compliance, and risk management. Traders and firms using algorithms must adhere to rules set by financial authorities to prevent market manipulation and ensure fair trading practices.
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Temporary Algorithmic Trader jobs near you
Infographic showing various Temporary Algorithmic Trader job openings in the United States as of July 2026, with employment types broken down into 35% Locum Tenens, 1% As Needed, 56% Full Time, 7% Part Time, and 1% Contract. Highlights an 84% Physical, 1% Hybrid, and 15% Remote job distribution, with an average salary of $96,774 per year, or $46.5 per hour.
GBM - Quantitative Dev/Strat - Systematic Rates Trading, New York

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

Goldman Sachs, Inc.

New York, NY

Other

Posted 3 days ago

New

Goldman Sachs rating

8.2

Company rating: 8.2 out of 10

Based on 26 frontline employees who took The Breakroom Quiz

44th of 148 rated banks

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.

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About Goldman Sachs

Sourced by ZipRecruiter

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1869

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