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Entry Level Quantitative Finance Jobs (NOW HIRING)

ROLE Entry-Level Quantitative Researchers are responsible for conducting rigorous quantitative ... S. or PhD in finance, economics, mathematics, statistics, data science, computer science, or other ...

ROLE Entry-Level Quantitative Researchers are responsible for conducting rigorous quantitative ... S. or PhD in finance, economics, mathematics, statistics, data science, computer science, or other ...

... of entry-level financial analysts for our rapidly growing Boston office. We are seeking an ... Responsibilities • Mapping and analyzing quantitative data • Preparing management reports • ...

Quantitative Researcher

New York, NY · Hybrid

$190K - $250K/yr

Experience Required: Entry-level (PhD Program) or Experienced (Postdoc, Faculty, Scientific Lab ... In our research-driven approach to the financial markets, our Chief Scientist oversees the group ...

Quantitative Researcher

New York, NY · On-site

$190K - $250K/yr

Experience Required: Entry-level (PhD Program) or Experienced (Postdoc, Faculty, Scientific Lab ... In our research-driven approach to the financial markets, our Chief Scientist oversees the group ...

Entry-Level Analyst U.S. citizenship required. Are you a critical thinker with acumen for problem ... quantitative science or business disciplines (Economics, Math, Statistics, Finance, Business ...

Job Summary The Financial Analyst I is an entry-level professional role responsible for supporting ... quantitative skills High attention to detail and data accuracy Proficiency with spreadsheets and ...

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Entry Level Quantitative Finance information

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$31K

$90.6K

$146K

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

As of Jul 20, 2026, the average yearly pay for entry level quantitative finance in the United States is $90,579.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,000.00 and $119,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Entry Level Quantitative Finance professional, and why are they important?

To thrive as an Entry Level Quantitative Finance professional, you need strong quantitative analysis skills, proficiency in mathematics and statistics, and typically a degree in math, finance, economics, engineering, or a related field. Familiarity with programming languages such as Python, R, or MATLAB, as well as experience with financial databases and risk management systems, is highly valued. Critical thinking, problem-solving abilities, and effective communication are essential soft skills for interpreting data and presenting findings to stakeholders. These skills enable individuals to analyze complex financial data, develop models, and support sound investment and risk management decisions.

What is the difference between Entry Level Quantitative Finance vs Entry Level Quantitative Analyst?

AspectEntry Level Quantitative FinanceEntry Level Quantitative Analyst
Required CredentialsBachelor's in Math, Finance, or related field; some roles prefer internshipsBachelor's in Math, Finance, or related field; often includes internships or relevant coursework
Work EnvironmentFinancial firms, hedge funds, investment banksFinancial institutions, asset management firms, hedge funds
Employer & Industry UsageCommonly used in finance industry for entry rolesOften used interchangeably with quantitative finance roles in finance sector

Entry Level Quantitative Finance and Entry Level Quantitative Analyst roles are similar, often requiring comparable educational backgrounds and working in similar financial environments. Both positions focus on data analysis, modeling, and supporting investment decisions, making them closely aligned in the finance industry.

What are some common challenges faced by entry-level professionals in quantitative finance, and how can they be addressed?

Entry-level professionals in quantitative finance often face challenges such as adapting to fast-paced, data-driven environments and quickly mastering complex financial models and programming languages. It's common to feel overwhelmed by the steep learning curve, especially when working with large datasets or developing algorithmic trading strategies. To address these challenges, new hires should proactively seek mentorship, participate in ongoing training, and collaborate closely with senior team members. Emphasizing continuous learning and open communication can help bridge knowledge gaps and foster a supportive team culture.

What is an entry level quantitative finance job?

An entry level quantitative finance job typically involves using mathematical models, statistical analysis, and programming to analyze financial data and support decision-making in areas like risk management, asset pricing, or trading. People in these roles often work at investment banks, hedge funds, or financial technology firms. Common titles include quantitative analyst (or 'quant'), research analyst, or risk analyst. These positions generally require strong analytical skills, proficiency in programming languages like Python, R, or MATLAB, and a background in mathematics, statistics, engineering, or physics.
More about Entry Level Quantitative Finance jobs
What cities are hiring for Entry Level Quantitative Finance jobs? Cities with the most Entry Level Quantitative Finance job openings:
What are the most commonly searched types of Quantitative Finance jobs? The most popular types of Quantitative Finance jobs are:
What states have the most Entry Level Quantitative Finance jobs? States with the most job openings for Entry Level Quantitative Finance jobs include:
Infographic showing various Entry Level Quantitative Finance job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 86% Full Time, 12% Part Time, and 1% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $90,579 per year, or $43.5 per hour.

Entry-Level Quantitative Developer

WallStreetQuants

Remote

Full-time

Posted 5 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.