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Remote Entry Level Quantitative Researcher Jobs (NOW HIRING)

WallStreetQuants

Entry-Level Quantitative Developer

... Entry-Level Quantitative Developer to join the team full-time. In this role, you will build ... research infrastructure. This remote role is open to candidates based across the United States ...

New

WestEd

Quantitative Research Associate

San Francisco, CA · On-site +1

The decision to allow remote work at the employee's convenience is based on the requirements of the ... At least three years' direct work experience in educational research, quantitative social science ...

Paxos Labs

DeFi Researcher

New York, NY · On-site +1

We're hiring a Quantitative Researcher to help scale Paxos Labs's DeFi risk analysis capabilities ... We also consider remote work on a case by case basis. Once we receive your application, we'll be in ...

WestEd

Quantitative Research Associate

San Francisco, CA · On-site +1

The decision to allow remote work at the employee's convenience is based on the requirements of the ... Strong knowledge of research and evaluation design and methodology, measurement, and quantitative ...

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Remote Entry Level Quantitative Researcher information

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$52.5K

$119.2K

$196.5K

How much do remote entry level quantitative researcher jobs pay per year?

As of Jul 17, 2026, the average yearly pay for remote entry level quantitative researcher in the United States is $119,165.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,500.00 and $152,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Entry Level Quantitative Researcher, and why are they important?

To thrive as a Remote Entry Level Quantitative Researcher, you need strong analytical skills, a solid foundation in statistics or mathematics, and at least a bachelor's degree in a quantitative field such as mathematics, statistics, computer science, or economics. Familiarity with programming languages like Python or R, data analysis tools, and statistical software (e.g., MATLAB, SAS, or Stata) is typically required. Critical thinking, attention to detail, and effective remote communication are important soft skills for collaborating with teams and presenting research findings. These skills ensure accurate data analysis and effective problem-solving, which are vital for generating actionable insights in a remote research environment.

What is a Remote Entry Level Quantitative Researcher?

A Remote Entry Level Quantitative Researcher is a professional who analyzes numerical data, develops statistical models, and helps solve complex problems for a company or organization while working from a remote location. This role typically involves tasks such as data collection, statistical analysis, and supporting research projects under the supervision of senior researchers. Entry level positions are designed for recent graduates or those new to the field, providing training and mentorship to build foundational quantitative skills. Working remotely allows for flexible location and often involves collaborating with teams through digital communication tools.

What is the difference between Remote Entry Level Quantitative Researcher vs Remote Data Analyst?

AspectRemote Entry Level Quantitative ResearcherRemote Data Analyst
Required CredentialsBachelor's in Math, Statistics, or related field; some roles may prefer internshipsBachelor's in Data Science, Statistics, or related field; certifications like SQL or Excel often preferred
Work EnvironmentResearch-focused, often in finance, tech, or consulting firms; collaborative teamsData-focused, in various industries including finance, healthcare, and marketing; often cross-functional teams
Employer & Industry UsageCommon in finance, tech, and consulting sectors; entry-level roles for research projectsWidespread across industries; entry-level roles for data analysis and reporting

Remote Entry Level Quantitative Researchers focus on developing models and analyzing data for research purposes, often in finance or tech. Remote Data Analysts interpret data sets to inform business decisions. While both roles require similar educational backgrounds, the researcher emphasizes modeling and theoretical analysis, whereas the analyst concentrates on data interpretation and reporting.

What are some common challenges faced by remote entry level quantitative researchers, and how can they be overcome?

Remote entry level quantitative researchers often encounter challenges such as limited access to immediate mentorship, difficulties in collaborating on complex data-driven tasks, and the need for effective self-management. To overcome these, it's helpful to proactively schedule regular check-ins with more experienced team members, utilize collaborative tools for data analysis, and maintain clear documentation of your work. Embracing open communication and seeking feedback can also help bridge the gap created by physical distance, ensuring both professional growth and successful project outcomes.
More about Remote Entry Level Quantitative Researcher jobs
What cities are hiring for Remote Entry Level Quantitative Researcher jobs? Cities with the most Remote Entry Level Quantitative Researcher job openings:
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What job categories do people searching Remote Entry Level Quantitative Researcher jobs look for? The top searched job categories for Remote Entry Level Quantitative Researcher jobs are:
Remote Entry Level Quantitative Researcher jobs near you
Infographic showing various Remote Entry Level Quantitative Researcher job openings in the United States as of July 2026, with employment types broken down into 80% Full Time, 10% Part Time, 5% Temporary, and 5% Contract. Highlights an 100% Remote job distribution, with an average salary of $119,165 per year, or $57.3 per hour.

Entry-Level Quantitative Developer

WallStreetQuants

Remote

Full-time

Posted 2 days ago

New

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.

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