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$39.5K

$96.8K

$269.5K

How much do temporary algorithmic trader jobs pay per year?

As of Aug 21, 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.

What is a temporary algorithmic trader?

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 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.

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.

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Temporary Algorithmic Trader jobs near you
Infographic showing various Temporary Algorithmic Trader job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 87% Full Time, 11% Part Time, and 1% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution, with an average salary of $96,774 per year, or $46.5 per hour.

Principal Engineer, State Estimation (R4602)

Shield AI

San Diego, CA

$270K - $400K/yr

Full-time

Re-posted 22 days ago

Job description

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

Job Description:
We are looking for an experienced state estimation engineer to design, develop, and support the deployment of safety-critical navigation solutions for aerospace platforms. This role requires deep expertise in state estimation theory, extensive practical experience implementing ownship navigation systems in the aerospace domain, and strong software development skills for production-quality navigation code. The engineer will design and implement a unified navigation architecture that supports traditional GNSS/IMU fusion while being extensible to all-source navigation strategies incorporating diverse sensing modalities for GPS-degraded and denied environments.
What you'll do:
Navigation System Architecture & Design:
  • Establish navigation performance requirements and error budgets for safety-critical applications 
  • Support decomposition of navigation requirements into allocations for sensors, estimation algorithms, and software components 
  • Design detailed software architecture for state estimation implementations, including module interfaces and data flow 
Algorithm Development & Implementation:
  • Design and implement Extended Kalman Filter algorithms for navigation applications, with broad understanding of state estimation theory and alternative filtering approaches 
  • Implement tightly-coupled and loosely-coupled GNSS/INS integration algorithms 
  • Integrate diverse sensing modalities (vision, RF, celestial etc.) into multi-sensor fusion framework for GPS-degraded environments 
  • Develop fault detection, isolation, and recovery (FDIR) strategies for navigation systems 
  • Implement integrity monitoring and protection level calculations for safety-critical operations 
Certification & Verification:
  • Develop verification and validation test plans for navigation algorithms 
  • onduct performance analysis including Monte Carlo simulation, covariance analysis, and flight test data evaluation 
  • Document navigation system design, requirements allocation, and compliance evidence 
  • Support safety assessment activities including failure modes and effects analysis 
Technical Leadership:
  • Provide technical guidance on navigation architecture and state estimation approaches 
  • Support trade studies evaluating navigation sensor suites and fusion strategies 
  • Mentor junior engineers on state estimation theory and implementation 
Required qualifications:
  • MS or PhD in Computer Science, Software Engineering, Electrical Engineering, Aerospace Engineering, Mechanical Engineering, Applied Mathematics, or related field 
    15+ years of experience developing state estimation algorithms for aerospace navigation applications 
  • Demonstrated experience implementing GNSS/INS integration solutions 
  • Experience with safety-critical system development and certification processes 
  • Deep understanding of state estimation theory 
  • Experience implementing multi-sensor fusion algorithms in production systems 
  • Strong background in inertial navigation, GNSS positioning, and sensor error modeling 
  • Strong programming skills in C/C++ and Python/MATLAB for algorithm development and analysis 
  • Understanding of integrity monitoring, protection levels, and safety assessment methods 
  • Experience with requirements management and verification/validation processes for certifiable systems 
  • Understanding of GPS/GNSS signal structure, error sources, and performance characteristics 
  • Knowledge of IMU error models, calibration, and Allan variance analysis 
  • Familiarity with alternative navigation sensors (camera, RF ranging, celestial, etc.) 
  • Understanding of navigation performance metrics (accuracy, integrity, continuity, availability)
  • Must be eligible to obtain a clearance
  • Ability to obtain a S//SAR level security clearance desired.
Preferred qualifications:
  • PhD in relevant field with focus on state estimation or navigation 
  • Direct involvement in certified navigation system development from requirements through flight test 
  • Experience with specialized navigation approaches (vision-aided navigation, terrain-referenced navigation, celestial navigation, etc.) 
  • Publications or patents in navigation or state estimation 
  • Experience with GPS/GNSS jamming and spoofing mitigation techniques 
$270,000 - $400,000 a year
#LI-SM1
#LF

Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
 
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
 
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
 
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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