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Entry Level Algorithmic Trading Jobs (NOW HIRING)

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Entry Level Algorithmic Trading information

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How much do entry level algorithmic trading jobs pay per hour?

As of Jul 23, 2026, the average hourly pay for entry level algorithmic trading in the United States is $22.48, according to ZipRecruiter salary data. Most workers in this role earn between $19.47 and $24.76 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Entry Level Algorithmic Trader, and why are they important?

To thrive as an Entry Level Algorithmic Trader, you need a solid understanding of quantitative analysis, statistics, and programming, often backed by a degree in finance, math, computer science, or a related field. Familiarity with programming languages like Python or C++, trading platforms, and market data systems is typically required. Strong problem-solving abilities, attention to detail, and the capacity to work under pressure are standout soft skills. These skills and qualities are crucial for developing, testing, and executing trading strategies efficiently and accurately in fast-paced financial markets.

What is an entry level algorithmic trading job?

An entry level algorithmic trading job typically involves helping to design, implement, and test automated trading strategies that buy and sell financial instruments in markets based on pre-defined algorithms. Professionals in this role usually work with programming languages such as Python or C++, analyze market data, and collaborate with quantitative analysts or senior traders. Entry-level positions often focus on supporting the development process, monitoring trading systems, and troubleshooting issues. These roles provide an excellent starting point for those interested in finance and technology, offering exposure to both financial markets and advanced programming.

What are some common challenges faced by entry-level algorithmic traders, and how can they be overcome?

Entry-level algorithmic traders often encounter challenges such as understanding complex market data, adapting to fast-paced environments, and debugging trading algorithms under time constraints. Collaborating closely with more experienced traders and developers, regularly reviewing code, and participating in knowledge-sharing sessions can help overcome these hurdles. Continuous learning and hands-on practice are crucial to building the confidence and technical proficiency needed to succeed in this dynamic field.
More about Entry Level Algorithmic Trading jobs
What cities are hiring for Entry Level Algorithmic Trading jobs? Cities with the most Entry Level Algorithmic Trading job openings:
What are the most commonly searched types of Algorithmic Trading jobs? The most popular types of Algorithmic Trading jobs are:
What states have the most Entry Level Algorithmic Trading jobs? States with the most job openings for Entry Level Algorithmic Trading jobs include:
Infographic showing various Entry Level Algorithmic Trading job openings in the United States as of July 2026, with employment types broken down into 25% Locum Tenens, 17% As Needed, 35% Full Time, 5% Part Time, and 18% Nights. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $46,753 per year, or $22.5 per hour.

Entry-Level Quantitative Developer

WallStreetQuants

Remote

Full-time

Posted 8 days ago


Job description

About the Role
A San Francisco-based proprietary trading firm expanding its quantitative team through a US-remote role is seeking a highly motivated Entry-Level Quantitative Developer to join the team full-time. In this role, you will build dependable research platforms, market-data systems, and trading technology as part of the firm's quantitative engineering team.
This is an ideal opportunity for early-career candidates who are passionate about software engineering, performance, market data, distributed systems, and quantitative finance. The work combines quantitative development, Python and C++ engineering, market data, low-latency systems, and algorithmic trading infrastructure. You will work closely with experienced traders, quantitative researchers, and engineers to learn how modern strategies, models, and trading systems are designed, tested, and implemented.
The team is small, technical, and collaborative, with direct access to experienced traders, quantitative researchers, engineers, high-quality market data, and modern research infrastructure.
This remote role is open to candidates based across the United States
Requirements
Responsibilities
- Build software for quantitative research, market data, simulation, and trading workflows.
- Improve system reliability, performance, testing, and operational visibility.
- Partner with researchers and traders to turn ideas into dependable tools.
- Develop reliable software used in quantitative research, trading, simulation, and market-data workflows.
- Design and maintain high-throughput data pipelines, APIs, and services for time-sensitive financial systems.
- Profile latency, memory use, reliability, and performance across critical research and trading applications.
- Write tests, participate in code reviews, and improve engineering standards across the codebase.
- Troubleshoot production issues and build monitoring that makes failures easier to detect and diagnose.
- Collaborate closely with traders and researchers to translate quantitative ideas into dependable tools.
Qualifications
- Early-career applicant from any degree discipline with practical software engineering ability.
- Transferable programming experience from a technology company, startup, research group, personal projects, or another setting.
- Interest in moving into quantitative development; no prior quant or finance experience is required.
- Open to applicants from any degree discipline, including people moving from technology, consulting, science, operations, or another career.
- Transferable professional, project, or self-directed experience that demonstrates analytical judgment and learning ability.
- Strong computer science fundamentals, including data structures, algorithms, testing, and systems design.
- Proficiency in Python, C++, Java, Rust, Go, or another production programming language.
- Ability to reason about performance, reliability, concurrency, and operational tradeoffs.
- Experience building substantial software through coursework, internships, open-source work, or personal projects.
- Interest in financial markets is useful, but prior finance experience is not required.
- Applicants from every degree discipline are welcome.
- No prior quantitative finance, trading, or investment-industry experience is required.
- Strong attention to detail, intellectual curiosity, and a commitment to continuous improvement.
- Excellent communication and teamwork skills.
Ideal Candidate
The ideal candidate is a pragmatic builder who cares about correctness, performance, and maintainability. You enjoy understanding how systems behave under real load, collaborating with demanding technical users, and taking ownership from initial design through testing and production support.
Benefits
What We Offer
- Hands-on development across quantitative systems, market data, research platforms, performance engineering, and production reliability.
- Mentorship from experienced quantitative traders, researchers, engineers, and technologists.
- Exposure to live markets, real financial datasets, and the full path from idea to implementation.
- A collaborative, high-performance environment that values curiosity, discipline, and continuous learning.
- Opportunities for rapid growth based on performance, ownership, and measurable impact.
- Competitive compensation and a benefits package aligned with the employer and location.