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Entry Level Quantitative Analyst Jobs (NOW HIRING)

... Entry-Level Quantitative Developer to join the team full-time. In this role, you will build ... analytical judgment and learning ability. - Strong computer science fundamentals, including data ...

ROLE Entry-Level Quantitative Researchers are responsible for conducting rigorous quantitative ... Follow, digest and analyze the latest academic research * Manage all aspects of the research ...

ROLE Entry-Level Quantitative Researchers are responsible for conducting rigorous quantitative ... Follow, digest and analyze the latest academic research * Manage all aspects of the research ...

Entry-Level Analyst U.S. citizenship required. Are you a critical thinker with acumen for problem ... If you like problem solving, working in a dynamic team environment, and quantitative analysis, this ...

This is an Entry-Level position, but candidates with 1-2 years of experience will be considered ... Responsibilities • Mapping and analyzing quantitative data • Preparing management reports • ...

You will execute quantitative analysis that translates data into actionable insights You will drive data driven decision making through the stakeholders You will influence new opportunities for ...

Quantitative Researcher

New York, NY · Hybrid

$190K - $250K/yr

Experience Required: Entry-level (PhD Program) or Experienced (Postdoc, Faculty, Scientific Lab ... Solid mathematical and analytical ability; exceptional problem-solving and modeling ability

Quantitative Researcher

New York, NY · On-site

$190K - $250K/yr

Experience Required: Entry-level (PhD Program) or Experienced (Postdoc, Faculty, Scientific Lab ... Solid mathematical and analytical ability; exceptional problem-solving and modeling ability

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Entry Level Quantitative Analyst information

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$56.5K

$133.9K

$240K

How much do entry level quantitative analyst jobs pay per year?

As of Jul 17, 2026, the average yearly pay for entry level quantitative analyst in the United States is $133,877.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $145,500.00 per year, depending on experience, location, and employer.

How much do entry level quant analysts make?

Entry-level quantitative analysts typically earn between $60,000 and $80,000 annually, depending on the industry, location, and educational background. Starting salaries can increase with proficiency in programming languages like Python or R, and familiarity with financial modeling and data analysis tools.

What does a typical day look like for an Entry Level Quantitative Analyst?

A typical day as an Entry Level Quantitative Analyst involves analyzing large data sets, building statistical models, and generating reports to support business or investment decisions. You may collaborate closely with other analysts, data scientists, or portfolio managers to interpret data and brainstorm solutions to complex problems. Daily tasks often include coding, data cleaning, and presenting findings to non-technical colleagues. Over time, you’ll gain exposure to more sophisticated projects and can take on greater responsibilities as your experience grows. This diverse workload helps develop both technical expertise and industry knowledge for future career advancement.

Can you get into quant without experience?

Entry level quantitative analyst roles typically require some background in mathematics, programming, or finance, but prior work experience is not always necessary. Strong analytical skills, proficiency in tools like Python or R, and relevant coursework or certifications can help candidates qualify. Internships or project work can also improve chances of entering the field without formal experience.

What are the key skills and qualifications needed to thrive in the Entry Level Quantitative Analyst position, and why are they important?

To thrive as an Entry Level Quantitative Analyst, you need strong analytical and mathematical skills, proficiency in statistical modeling, and a degree in a quantitative field such as mathematics, statistics, finance, or computer science. Familiarity with programming languages like Python, R, or SQL and experience using data analysis tools such as Excel, MATLAB, or statistical software are often expected. Excellent problem-solving abilities, communication skills, and attention to detail will help you stand out in this position. These competencies enable you to interpret complex data, deliver actionable insights, and collaborate effectively within fast-paced, data-driven teams.

Will AI replace quant analysts?

AI can automate certain tasks performed by quantitative analysts, such as data analysis and model testing, but it is unlikely to fully replace the role. Quantitative analysts will continue to be essential for developing complex models, interpreting results, and making strategic decisions that require human judgment and expertise. Skills in programming, statistical analysis, and financial knowledge remain valuable in this evolving field.

Is 40 too old to become a quant?

Entry level quantitative analyst roles typically require strong mathematical, programming, and statistical skills, which can be developed at any age. Age is generally not a barrier if you have relevant education, experience, and the ability to learn new tools like Python or R; many professionals transition into quant roles later in their careers.

What is an Entry Level Quantitative Analyst job?

An Entry Level Quantitative Analyst uses mathematical models, statistical techniques, and data analysis to support financial decision-making. They typically work in finance, investment, or risk management, analyzing market trends, evaluating trading strategies, or assessing risk. This role requires strong analytical skills, programming proficiency (often in Python, R, or SQL), and knowledge of financial concepts. It serves as a foundation for more advanced quantitative roles, providing hands-on experience with real-world data and financial models.

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Entry-Level Quantitative Developer

WallStreetQuants

Remote

Full-time

Posted 3 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.