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Remote Junior Quant Trader Jobs (NOW HIRING)

MLabs

Head of Growth - Hyperliquid Agents

$150K - $200K/yr

Remote Americas preferred location Remote Full-time Compensation: $150k-$200k base plus equity ... Experience in perpetual, algorithmic, or quantitative trading; background in developer-facing ...

Wintermute

DeFi Algorithmic Trader

New York, NY · On-site +1

Experience with programmatic statistical analysis and quantitative / analytic skills * High level ... Although we are unable to accept fully remote candidates, we support significant flexibility in ...

Old Mission

Python Software Engineer

Chicago, IL · On-site +1

$150K - $225K/yr

Additionally, you'll collaborate closely with quants, traders, and research teams to bolster our ... In office M-F with 10 remote days per year Base Salary Range $150,000 - $225,000 - Salaries are ...

Old Mission

Python Software Engineer

New York, NY · On-site +1

$150K - $225K/yr

Additionally, you'll collaborate closely with quants, traders, and research teams to bolster our ... In office M-F with 10 remote days per year Base Salary Range $150,000 - $225,000 - Salaries are ...

WallStreetQuants

Creative Producer

WallStreetQuants is a fast-growing education business in the quant trading space. We help people ... Full remote, flexible hours, async-first culture * Real growth path: this role can grow into ...

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How much do remote junior quant trader jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for remote junior quant trader in the United States is $26.96, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $33.17 per hour, depending on experience, location, and employer.

What is a remote junior quant trader?

A Remote Junior Quant Trader is an entry-level quantitative analyst who works from a remote location to develop, test, and implement trading strategies using mathematical models and statistical techniques. They analyze large sets of financial data to identify trading opportunities, manage risk, and optimize profitability. Typically, they work as part of a team under the guidance of senior traders and may use programming languages such as Python or R to build their models. This role is ideal for individuals with strong analytical skills and an interest in financial markets, offering flexibility to work from anywhere with an internet connection.

What are the key skills and qualifications needed to thrive as a remote junior quant trader?

To thrive as a Remote Junior Quant Trader, you need a strong background in mathematics, statistics, and programming (typically Python or C++), often supported by a degree in a quantitative field. Familiarity with trading platforms, data analysis tools (like MATLAB or R), and financial market data systems is commonly required. Problem-solving ability, attention to detail, and effective communication are crucial soft skills for this role. These skills ensure accurate strategy development, efficient execution, and productive collaboration, which are vital for success in the fast-paced trading environment.

What are some common challenges faced by remote junior quant traders, and how can they be addressed?

Remote junior quant traders often face challenges such as limited real-time collaboration with senior team members, managing time effectively without in-person supervision, and staying updated with rapidly changing market conditions. To overcome these, it's important to proactively communicate through regular virtual meetings, utilize collaborative tools for code sharing and analysis, and stay disciplined with structured work hours. Additionally, seeking mentorship and participating in team discussions can help bridge the gap and accelerate learning in a remote setting.
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Remote Junior Quant Trader jobs near you
Infographic showing various Remote Junior Quant Trader job openings in the United States as of August 2026, with employment types broken down into 93% Full Time, and 7% Part Time. Highlights an 7% In-person, and 93% Remote job distribution, with an average salary of $56,068 per year, or $27 per hour.

Senior Machine Learning Engineer

The Voleon Group

Berkeley, CA • On-site, Remote

$290K - $395K/yr

Full-time

Re-posted 20 days ago

Job description

Voleon is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. For nearly two decades, we have led our industry and worked at the frontier of applying AI/ML to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future.
Your colleagues will include internationally recognized experts in artificial intelligence and machine learning research as well as highly experienced finance and technology professionals. In addition to our enriching and collegial working environment, we offer highly competitive compensation and benefits packages, technology talks by our experts, a beautiful modern office, daily catered lunches, and more.
As a Senior Machine Learning Engineer on one of Voleon's Research teams, you will partner directly with research staff to advance our quantitative trading strategies. You will translate novel research ideas into production-quality code, build and maintain the data pipelines and modeling infrastructure that underpin our strategies, and apply your own strong mathematical intuition to solve open-ended technical challenges.
This role lives at the boundary of research and engineering. You will be expected to understand the statistical and mathematical concepts your research partners work with, contribute meaningfully to technical discussions about model design and evaluation, and ensure that the resulting systems are performant, reliable, and maintainable. You will work at the intersection of Computer Science, Mathematics, and Statistics - building high-performance tools that enable world-class research while maintaining a high engineering standard.
Responsibilities
  • Partner with PhD researchers to design, implement, and productize machine learning models that drive quantitative trading strategies
  • Develop and maintain complex data pipelines, including data ingestion, feature engineering, validation, and quality monitoring
  • Translate research prototypes and novel ideas into performant, well-tested, production-ready code
  • Build extensible tools and frameworks that accelerate the model development and experimentation lifecycle
  • Supervise, understand, and remediate subtle data quality issues across both research and production environments
  • Proactively lead projects from requirements through delivery, making autonomous decisions about scope, dependencies, and trade-offs, with an emphasis on long-term maintainability
  • Coordinate and contribute to deployment efforts while guiding junior engineers and researchers; align with research and engineering stakeholders on ownership, execution, and prioritization
  • Foster engineering consistency, standards, and best practices within Research

Requirements
  • Bachelor's degree (or higher) in Computer Science, Applied Mathematics, Statistics, or a related quantitative field
  • 5+ years of professional software engineering experience, with strong CS fundamentals (data structures, algorithms, systems design)
  • Demonstrated mathematical maturity - comfort with the concepts and notation used in statistics, linear algebra, optimization, and probability
  • Deep proficiency in Python; experience with R and/or C/C++ is a strong plus
  • Extensive experience with numerical and data science libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar)
  • Proven experience building or maintaining machine learning systems in a distributed computing environment
  • Proficiency developing in a Linux environment with attention to performance, correctness, and reproducibility
  • Exceptional attention to detail, particularly when working with imperfect or heterogeneous data
  • Strong verbal and written communication skills, and the ability to collaborate effectively with researchers whose primary expertise is not software engineering

Preferred Qualifications
  • Experience with experiment management, model evaluation pipelines, or ML workflow orchestration
  • Familiarity with modern ML/AI infrastructure patterns (model serving, feature stores, distributed training)
  • Experience with performance profiling and optimization of numerical or modeling code
  • Prior exposure to financial data, time-series analysis, or quantitative research environments

"Friends of Voleon" Candidate Referral Program
If you have a great candidate in mind for this role and would like to have the potential to earn $15,000 if your referred candidate is successfully hired and employed by The Voleon Group, please use this form to submit your referral. For more details regarding eligibility, terms and conditions please make sure to review the Voleon Referral Bonus Program.
Equal Opportunity Employer
The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.
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About Voleon Group

Sourced by ZipRecruiter

Industry

Investment management and consulting services

Company size

11 - 50 Employees

Headquarters location

Berkeley, CA, US

Year founded

2007

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