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Quant Developer Jobs in Washington, DC (NOW HIRING)

CPMC LLC

Sr. Developer

Greenbelt, MD · Remote

$55.75 - $73.75/hr

CPMC is seeking a Senior Developer for the United States Census Bureau's Disclosure Avoidance ... Quantitative Management: Ability to determine process measures and track to determine process ...

E-Solutions

Sr. Python Developer | McLean, VA

Mclean, VA · On-site

$124K - $167K/yr

... quantitative discipline • Prior experience with financial services companies desired but not necessary Required Skills : Jenkins,Python Additional Skills : Software Developer

BTree Solutions, Inc.

UI/UX DEVELOPER

Mclean, VA · On-site

$50.75 - $66/hr

Bachelor's degree, ideally in Computer Science, Financial Engineering or a related quantitative discipline * Prior experience with financial services companies desired but not necessary

Air

Implementation Engineer

Arlington, VA

Implementation Engineers at Air have a quantitative mindset and firm understanding of how to use technology and data to solve hard customer problems. Implementation Engineers are responsible for ...

CPMC LLC

Sr. Developer (USCB)

Greenbelt, MD · Remote

$55.75 - $73.75/hr

CPMC is seeking a Senior Developer for the United States Census Bureau's Disclosure Avoidance ... Quantitative Management: Ability to determine process measures and track to determine process ...

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All JobsQuant Developer JobsQuant Developer Jobs in Washington, DC

Quant Developer information

See Washington, DC salary details

$111K

$192.2K

$293.8K

How much do quant developer jobs pay per year?

As of Jun 27, 2026, the average yearly pay for quant developer in Washington, DC is $192,163.00, according to ZipRecruiter salary data. Most workers in this role earn between $152,300.00 and $225,300.00 per year, depending on experience, location, and employer.

How much do quant devs make?

Quant developers typically earn between $100,000 and $200,000 annually, with experienced professionals and those at top firms earning over $300,000 including bonuses. Compensation often depends on experience, location, and the complexity of the models they develop, with many roles requiring strong programming skills in languages like Python or C++ and knowledge of financial markets.

What is a Quant Developer job?

A Quant Developer (Quantitative Developer) is a software engineer who builds and maintains financial models, trading systems, and analytical tools for quantitative analysts and traders. They use programming languages like Python, C++, or Java to develop algorithms that automate trading strategies, risk analysis, and data processing. Quant Developers typically work in hedge funds, investment banks, or proprietary trading firms, collaborating with quants and portfolio managers to optimize trading performance. Strong mathematical skills, proficiency in financial markets, and expertise in software development are essential for this role.

Does JP Morgan hire quants?

JP Morgan actively hires quantitative analysts and developers for roles in trading, risk management, and technology. These positions typically require strong programming skills, knowledge of financial models, and often a background in mathematics or engineering. The firm offers opportunities for quants across various teams and locations, with competitive hiring standards and onboarding processes.

What are some typical challenges quant developers face in their daily work?

Quant developers often work with large, complex datasets and real-time data streams, which can present technical challenges related to performance, accuracy, and scalability. They may need to continuously adapt to changing market requirements or new financial regulations, requiring staying up to date and learning new tools or methods. Collaboration with quants, traders, and other stakeholders is common, so balancing technical problem-solving with effective communication is also important. These challenges make the role both demanding and intellectually rewarding for those passionate about technology and finance.

Is quant developer a good career?

A quant developer is a highly specialized role that involves developing algorithms and models for financial trading and risk management. It typically requires strong programming skills in languages like Python or C++, along with a background in mathematics or finance. The role offers high earning potential and demand in financial firms but often involves long hours and high pressure.

What are the key skills and qualifications needed to thrive in the Quant Developer position, and why are they important?

To thrive as a Quant Developer, you need advanced programming skills (often in Python, C++, or Java), a strong foundation in mathematics or statistics, and a relevant degree such as in computer science, engineering, or quantitative finance. Expertise in numerical libraries, version control systems like Git, and familiarity with financial modeling tools or industry data feeds is highly valuable. Collaboration, strong analytical thinking, and the ability to communicate complex concepts clearly are critical soft skills for this role. These capabilities are essential for designing robust quantitative models and working effectively with cross-functional teams in fast-paced financial environments.

Is 30 too late to become a quant?

Quantitative analyst roles typically require strong backgrounds in mathematics, programming, and finance, often gained through advanced degrees or relevant experience. While starting a career at 30 is possible, it may require additional training or certifications such as a master's in financial engineering or programming skills in Python or C++. Age is less important than skills, experience, and the ability to adapt to a fast-paced, technical environment.
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Quant Developer jobs near you
Infographic showing various Quant Developer job openings in Washington, DC as of June 2026, with employment types broken down into 14% Internship, 58% Full Time, and 28% Contract. Highlights an 100% In-person job distribution, with an average salary of $192,163 per year, or $92.4 per hour.
Machine Learning Engineer USC

Machine Learning Engineer USC

Connexions Data Inc

Arlington, VA • On-site

Other

Posted 14 days ago

Job description

Machine Learning Engineer

Start: IMMED

Duration: 06 - 12 months + Extension

Location: Arlington, VA

Type: W2 only

***Active Secret Clearance Required***

Position Overview

The Machine Learning Engineer will develop and validate quantitative models that translate organizational workload drivers into defensible Full-Time Equivalent (FTE) requirements across military, civilian, and contractor workforces. This role will work closely with Data Scientists, AI Engineers, and functional stakeholders to build scalable workforce planning and forecasting solutions using advanced statistical and machine learning techniques.

Education

Bachelor s Degree Required

Advanced degree preferred in:

  • Mathematics
  • Statistics
  • Econometrics
  • Economics

Required Skills

  • Machine Learning Modeling
  • Econometrics
  • Classical Regression Modeling
  • Statistics
  • Python

Preferred Skills

  • Palantir
  • Workforce Forecasting
  • Workload Modeling
  • AI and Data Testing

Day-to-Day Responsibilities

  • Build and validate quantitative workforce planning and forecasting models.
  • Translate organizational workload drivers into FTE requirements across military, civilian, and contractor populations.
  • Collaborate with Senior Data Scientists and AI Engineers to explore, analyze, and prepare data.
  • Perform feature engineering using Army personnel systems, including:
    • IPPS-A
    • DAPES
    • TAADS-R
  • Develop and calibrate regression models and plausibility banding logic.
  • Integrate scenario-planning model parameters into front-end applications.
  • Ensure model outputs are traceable, explainable, and defensible during client validation reviews.
  • Support AI and workforce analytics initiatives through statistical analysis and model testing.
  • Work with functional leads to validate assumptions, methodologies, and outputs.

Expected Deliverables

  • Automated manpower requirement determination models.
  • Data-driven workforce forecasting solutions.
  • Quantitative workforce planning outputs supported by defensible statistical methodologies.
  • Validated machine learning and regression-based forecasting models.
  • Reporting and analytics outputs supporting manpower and resource planning decisions.

Ideal Candidate Profile

  • Experience developing machine learning and statistical forecasting models.
  • Strong background in regression analysis, econometrics, and workforce analytics.
  • Proficiency in Python for data science and machine learning applications.
  • Ability to explain complex modeling approaches to both technical and non-technical stakeholders.
  • Experience working with large government or enterprise workforce datasets is highly preferred.

Apply