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Quant Engineer Jobs in Baltimore, MD (NOW HIRING)

Mondo

DevOps Engineer

Owings Mills, MD · On-site

$55 - $63/hr

This position is not eligible for sponsorship Our client is seeking a DevOps Engineer to join its Quant Analytics Platforms team within the Chief Data Office. This team is responsible for building ...

Deloitte

Data Engineer II

Baltimore, MD · On-site

$113K - $136K/yr

Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, Information Systems, Data Science, or a quantitative field * 3+ years of experience designing, building, and ...

Deloitte

Data Engineer II

Baltimore, MD

$113K - $136K/yr

Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, Information Systems, Data Science, or a quantitative field * 3+ years of experience designing, building, and ...

Deloitte

Data Engineer II

Baltimore, MD · On-site

$113K - $136K/yr

Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, Information Systems, Data Science, or a quantitative field * 3+ years of experience designing, building, and ...

Deloitte

Data Engineer II

Baltimore, MD · On-site

$113K - $136K/yr

Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, Information Systems, Data Science, or a quantitative field * 3+ years of experience designing, building, and ...

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Quant Engineer information

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$37.8K

$90K

$149.5K

How much do quant engineer jobs pay per year?

As of Aug 26, 2026, the average yearly pay for quant engineer in Baltimore, MD is $89,962.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,000.00 and $99,400.00 per year, depending on experience, location, and employer.

What is a quant engineer?

Quant Engineers, or quantitative engineers, are professionals who apply mathematical models, statistical techniques, and computer programming to solve complex problems in finance and related industries. They often work on designing trading algorithms, risk management tools, and pricing models for financial instruments. Quant Engineers typically have strong backgrounds in mathematics, computer science, and finance, and are skilled in programming languages such as Python, C++, or R. Their work helps financial firms make data-driven decisions and optimize strategies in highly competitive markets.

How do quant engineers typically collaborate with traders and other team members to develop and implement trading strategies?

Quant Engineers work closely with traders, researchers, and software developers to design, test, and refine quantitative trading models. They often translate mathematical models into efficient code, analyze large datasets, and ensure strategies are both robust and scalable for real-time trading environments. Frequent communication is key, as Quant Engineers must gather requirements from traders, iteratively backtest ideas, and adapt models based on feedback and market changes. This collaborative process helps ensure strategies are both scientifically sound and practically viable for deployment.

What are the key skills and qualifications needed to thrive as a quant engineer, and why are they important?

To thrive as a Quant Engineer, you need strong quantitative and programming skills, typically supported by a degree in mathematics, physics, computer science, or a related field. Proficiency in programming languages such as Python, C++, or Java, as well as familiarity with statistical analysis tools and financial modeling systems, is essential. Analytical thinking, problem-solving abilities, and effective communication distinguish top performers in this role. These skills enable Quant Engineers to develop robust models and algorithms that drive accurate trading strategies and risk management in fast-paced financial environments.

What is the difference between Quant Engineer vs Quant Analyst?

AspectQuant EngineerQuant Analyst
Required CredentialsDegree in Math, Finance, or Computer Science; often requires programming skillsDegree in Finance, Economics, or Math; less emphasis on programming
Work EnvironmentDevelops models, algorithms, and software tools for trading and risk managementAnalyzes data, interprets models, and provides insights for trading strategies
Employer & Industry UsageFinancial firms, hedge funds, investment banksFinancial firms, asset management, hedge funds

While both roles involve quantitative analysis, Quant Engineers focus on building and implementing models and software, whereas Quant Analysts primarily analyze data and interpret models to inform trading decisions. The roles often overlap but differ in technical depth and responsibilities.

What are popular job titles related to Quant Engineer jobs in Baltimore, MD?

For Quant Engineer jobs in Baltimore, MD, the most frequently searched job titles are:

What job categories do people searching Quant Engineer jobs in Baltimore, MD look for?

The top searched job categories for Quant Engineer jobs in Baltimore, MD are:

What cities near Baltimore, MD are hiring for Quant Engineer jobs?

Cities near Baltimore, MD with the most Quant Engineer job openings:

Quant Engineer jobs near you
Infographic showing various Quant Engineer job openings in Baltimore, MD as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $89,962 per year, or $43.3 per hour.

Quantitative Investment Analyst - Multi-Asset

Baltimore, MD • Hybrid

T Rowe Price
Funds, Trusts and Financial Programs • 5 - 10K employees

9.1

Company rating: 9.1 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

Great coworkers

People enjoy working here

Good employer

Learn more about T Rowe Priceexternal

Full-time

Re-posted 8 days ago

Job description

About the Team

T. Rowe Price's Multi-Asset Division collectively manages $550bn+ across a growing range of global retirement mandates and provides a collaborative, outcome-oriented environment for quantitative researchers from diverse academic and professional backgrounds.

Role Summary

The Quantitative Investment Analyst role in the Multi-Asset Division is intended for an experienced, highly quantitatively skilled candidate who will join the Lifecycle Research team responsible for setting the strategic asset allocation of target date strategies and for developing personalized retirement investment solutions. Researchers on the team build analytical frameworks and conduct rigorous quantitative studies related to various aspects of retirement investing. Main areas of focus span individual investor behavior, target date glide path construction and customization, personalized financial advice, household finance, and design of pooled and personalized retirement income solutions. In addition to deep, topic-specific research, the role requires active contribution to the team's analytical infrastructure. Responsibilities include reviewing and updating quantitative models, curating core datasets, and partnering closely with quantitative developers to implement scalable, production-quality code.

The research environment at T. Rowe Price is highly interactive and places a strong emphasis on integrity, collaboration, and intellectual agility. Successful candidates demonstrate pragmatism, comfort with ambiguity, and a constructive approach to feedback and change. We seek individuals with a development mindset and a genuine interest in building comprehensive, robust analytical systems that shape investment outcomes for millions of retirement savers worldwide. Prior financial industry experience is not required.

Responsibilities

  • Execute all stages of quantitative research, from project design to communicating results to the key stakeholders internally and externally
  • Extend and maintain the team's analytical and reporting infrastructure; this encompasses stewardship of core datasets, statistical models, and shared codebases
  • Disseminate research findings: participate in industry conferences and webinars, write white papers, and publish in peer-reviewed journals

Qualifications

Required:

  • Graduate degree in a STEM field
  • Strong foundation in applied data science (e.g., experimental research in natural sciences, statistics, finance, or econometrics)
  • Demonstrated programming proficiency, including developing and extending object-oriented, version-controlled code in MATLAB, Python, or Java
  • Collaborative working style: willingness to listen, penchant for sharing knowledge, and responsiveness to business needs
  • Ability to clearly convey complex analytical concepts and results to audiences with varying levels of technical expertise

Preferred:

  • Ph.D. in a STEM field
  • Expertise in operations research, optimization, and stochastic modeling
  • Demonstrated interest in applied research in lifecycle investing, quantitative financial planning, or adjacent fields
  • Prior experience conducting applied research in a business environment
  • Experience working within a software or research infrastructure development workflow

FINRA Requirements

FINRA licenses are not required and will not be supported for this role.

Work Flexibility

This role is eligible for hybrid work, with up to one day per week from home.

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