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Quantitative Risk Manager Jobs in Massachusetts (NOW HIRING)

Fidelity Investments

Quantitative Analyst

Boston, MA · On-site

$100K - $200K/yr

The Team SAI's Quantitative Research analysts work either directly on an asset class or product ... managed by SAI. The team's work includes risk modeling, portfolio construction analysis, the ...

MFS

Quant Research Associate

Boston, MA · Hybrid

$10K/mo

The Quantitative Research Associates work with analysts and portfolio managers through the development and maintenance of risk management and portfolio construction processes. Quantitative Research ...

Fidelity Investments

Quantitative Analyst

Boston, MA · On-site

$100K - $200K/yr

... managed by SAI. The team's work includes risk modeling, portfolio construction analysis, the ... The Role The Quantitative Taxable team within Quantitative Research group is responsible for ...

Fidelity Investments

Quantitative Analyst

Boston, MA

$100K - $200K/yr

... managed by SAI. The team's work includes risk modeling, portfolio construction analysis, the ... The Role The Quantitative Taxable team within Quantitative Research group is responsible for ...

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All JobsQuantitative Risk JobsQuantitative Risk Manager JobsQuantitative Risk Manager Jobs in Massachusetts

Quantitative Risk Manager information

See Massachusetts salary details

$56.2K

$121.8K

$185.7K

How much do quantitative risk manager jobs pay per year?

As of Jul 25, 2026, the average yearly pay for quantitative risk manager in Massachusetts is $121,833.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,300.00 and $140,900.00 per year, depending on experience, location, and employer.

What can I do with a quantitative risk management degree?

A degree in quantitative risk management prepares individuals for roles such as risk analyst, risk manager, or quantitative analyst in finance, insurance, or consulting firms. These roles involve assessing and modeling financial risks using statistical tools, programming languages like Python or R, and risk management frameworks. Professionals in this field often work with regulatory compliance and may pursue certifications like FRM or PRM.

What is the salary of a quant risk manager?

A quantitative risk manager's salary typically ranges from $100,000 to $200,000 annually, with higher compensation often associated with experience, advanced degrees, and certifications such as FRM or CFA. In addition to base salary, bonuses and performance incentives can significantly increase total compensation in this role.

What does a quantitative risk manager do?

A quantitative risk manager analyzes financial data and models to identify, measure, and manage risks within an organization. They use statistical techniques, programming skills, and risk management tools to develop strategies that minimize potential losses and ensure regulatory compliance.

How does a Quantitative Risk Manager typically collaborate with other departments within a financial institution?

Quantitative Risk Managers work closely with teams such as trading, compliance, IT, and senior management to identify, measure, and mitigate financial risks. They often translate complex quantitative models into actionable insights for non-technical stakeholders and facilitate the integration of risk metrics into daily decision-making processes. Collaboration is essential for ensuring that risk assessments align with business objectives and regulatory requirements, often requiring regular cross-functional meetings and clear communication.

What are the key skills and qualifications needed to thrive as a Quantitative Risk Manager, and why are they important?

To thrive as a Quantitative Risk Manager, you need strong analytical abilities, a deep understanding of statistics and financial mathematics, and typically an advanced degree in finance, mathematics, or a related field. Proficiency in programming languages like Python or R, experience with risk modeling software, and certifications such as FRM or CFA are highly valuable. Exceptional problem-solving, communication, and collaboration skills help you convey complex risk metrics to stakeholders and work effectively in cross-functional teams. These skills ensure accurate risk assessments, regulatory compliance, and informed decision-making in dynamic financial environments.

How much do quant risk managers make?

Quantitative risk managers typically earn between $100,000 and $200,000 annually, with senior roles and those in major financial centers earning higher salaries. Compensation often includes bonuses and benefits, and strong skills in mathematics, programming, and risk modeling are essential for higher-paying positions.

What is a Quantitative Risk Manager?

A Quantitative Risk Manager is a professional who uses mathematical models, statistical analysis, and quantitative techniques to identify, measure, and manage financial risks within an organization. They often work in banks, investment firms, or insurance companies to analyze market, credit, and operational risks. Their responsibilities include developing risk models, monitoring risk exposures, and advising senior management on risk mitigation strategies. They play a key role in ensuring that organizations make informed decisions and comply with regulatory requirements.

What is the difference between Quantitative Risk Manager vs Quantitative Analyst?

AspectQuantitative Risk ManagerQuantitative Analyst
Primary FocusAssessing and managing risk exposure across financial portfoliosDeveloping models and algorithms for investment strategies
Required CredentialsAdvanced degrees in finance, mathematics, or related fields; certifications like FRM or CFADegrees in finance, mathematics, or statistics; often pursuing CFA or similar
Work EnvironmentFinancial institutions, risk management departmentsInvestment firms, hedge funds, banks
Key SkillsRisk assessment, regulatory knowledge, quantitative modelingData analysis, programming, financial modeling

While both roles involve quantitative skills and financial knowledge, Quantitative Risk Managers focus on identifying and mitigating risks within organizations, whereas Quantitative Analysts primarily develop models to inform investment decisions. Understanding these differences helps professionals choose the right career path or job search focus.

What are the most commonly searched types of Quantitative Risk jobs in Massachusetts? The most popular types of Quantitative Risk jobs in Massachusetts are:
What are popular job titles related to Quantitative Risk Manager jobs in Massachusetts? For Quantitative Risk Manager jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Quantitative Risk Manager jobs in Massachusetts look for? The top searched job categories for Quantitative Risk Manager jobs in Massachusetts are:
What cities in Massachusetts are hiring for Quantitative Risk Manager jobs? Cities in Massachusetts with the most Quantitative Risk Manager job openings:
Quantitative Risk Manager jobs near you
Infographic showing various Quantitative Risk Manager job openings in Massachusetts as of July 2026, with employment types broken down into 83% Full Time, 15% Part Time, and 2% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $121,833 per year, or $58.6 per hour.
Quantitative Trading Analyst

Quantitative Trading Analyst

Wellington Management

Boston, MA

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 10 days ago

Job description

About Us

Wellington Management offers comprehensive investment management capabilities that span nearly all segments of the global capital markets. Our investment solutions, tailored to the unique return and risk objectives of institutional clients in more than 60 countries, draw on a robust body of proprietary research and a collaborative culture that encourages independent thought and healthy debate. As a private partnership, we believe our ownership structure fosters a long-term view that aligns our perspectives with those of our clients.

About the Role

THE DEPARTMENT

Investment Implementation & Trading transforms investment decisions into high-quality portfolio implementation across global markets. The department brings together portfolio construction, global trading, trading research, treasury, middle office, and trading risk management to improve execution quality, trading efficiency, and investment outcomes. Its internally developed trading technology and proprietary data platforms provide a competitive advantage and underpin Wellington's research and electronic trading strategy.

THE TEAM

The Trading Research & Analytics (TRA) team is the quantitative research and analytics function supporting Wellington's global trading organization.

We partner directly with traders, portfolio managers, broker-dealers, and clients to improve execution outcomes through quantitative research, data science, and systematic trading analytics. Our work sits at the intersection of electronic trading, transaction cost analysis, and market microstructure.

Rather than simply measuring trading performance, our mission is to continuously improve it.

We develop the data, models, and research that help answer questions such as:

  • Which execution strategy should be used?

  • When should an order be executed?

  • How much should we expect a trade to cost?

  • What execution price should we be willing to pay?

  • Which dealers consistently deliver the best outcomes?

  • How can systematic trading strategies improve client alpha?

As our trading platform continues to evolve, the team is expanding beyond traditional transaction cost analysis into predictive modeling, execution optimization, and AI-assisted trading research.

THE ROLEANDWHAT YOU'LL DO

We are seeking a Quantitative Trading Analyst to join Trading Research & Analytics and help improve execution outcomes through research, analytics, and systematic decision support.

Quantitative Trading Research

Conduct empirical research on trading behavior, market microstructure, liquidity, and execution performance across global fixed income markets. Translate ambiguous business questions into testable research hypotheses and develop statistical, optimization, and machine learning models that improve execution decisions and investment outcomes.

Transaction Cost Analysis & Execution Analytics

Design and enhance Wellington's fixed income TCA framework, including pre- and post-trade cost models, implementation shortfall analytics, dealer scorecards, execution benchmarking, and best execution reporting. Use quantitative analysis toidentifypractical opportunities to improve execution quality.

Fixed IncomeMarket Structure Research

Partner with fixed income traders to analyze execution across Global Investment Grade Credit, Global High Yield, Emerging Markets Debt, Securitized Credit, and Agency Mortgages. Track market structure, electronic trading, dealer behavior, RFQ protocols, and liquidity trends to recommend enhancements to Wellington's trading capabilities.

Systematic Trading & Decision Support

Build research and analytical tools that help traders and portfolio managers make better execution decisions. Evaluate execution strategies, dealerselection, liquidity conditions, and timing to support systematic trading workflows and improve outcomes.

Trading Data & Research Platform

Own the analytical representation of trading data and partner with technology teams to build scalable research datasets across the trading lifecycle. Maintain production-quality research infrastructure that combines OMS, EMS, market, pricing, and portfolio data with strong data quality, business logic, reproducibility, and analytical integrity.

Partnership & Influence

Collaborate with portfolio managers, traders, broker-dealers, technology teams, and senior leaders to translate research into practical trading decisions. Communicate complex findings clearly and help shape Wellington's execution strategy, trading technology, and research capabilities.

QUALIFICATIONS

Education & Experience

  • Bachelor's degreerequired; master's or PhD in Statistics, Mathematics, Economics, Computer Science, Engineering, Finance, or a related quantitative disciplineconsidered favorably.

  • 5-7 years of relevant experience in quantitative trading research, execution analytics, TCA, systematic trading, quantitative investment research, or advanced analytics in an institutionalmarketsenvironment.

  • Hands-on experience supporting institutional fixed income trading, preferably across Investment Grade Credit, High YieldCredit, Emerging Markets Debt, SecuritizedCredit, or Agency Mortgages.

Quantitative Research & Modeling

  • Proficient capability in analytics and quantitative research, with experience cleaning messy real-world data, developing visualizations, generating reports, and using descriptive analytics to explain what happened and diagnostic analytics to explain why it happened.

  • Ability to move beyond reporting into research: formulate trading, execution, liquidity, and portfolio implementation questions as testable hypotheses using statistics, algebra, mathematical reasoning, and data-driven inference.

  • Hands-on experience building,validating, and interpreting predictive models, transaction cost models, optimization frameworks, machine learning models, or AI-assisted research workflows used in trading or execution analytics.

  • Experience analyzing real-world trading datasets, including orders, executions, quotes, dealer responses, benchmarks, prices, liquidity signals, and portfolio attributes.

  • Interest in applying machine learning, natural language processing, or modern AI techniques to trading research, predictive analytics, data quality, automation, or decision support.

Technical Skills

Required:

  • Expert-level Python skills for quantitative research, modeling, data engineering, and production-quality analytical development, including solid understanding of object-oriented programming, when to use OOP versus procedural scripts/functions, and how to structure reusable, maintainable code.

  • Proficient SQL skills, including fundamentals of querying data with SELECT, WHERE, ORDER BY, COUNT, SUM, AVG, GROUP BY, HAVING, CASE WHEN, and NULL behavior; strong understanding of joins, cardinality, duplicate handling, joins versus subqueries, window functions, and subqueries/CTEs.

  • Fluency with modern Python research and modeling libraries, including pandas for real-world and messy data, NumPy for vectorized thinking, and scikit-learn for machine learning workflows.

  • Experience using Git, reproducible research workflows, code review, testing, and documentation tomaintainanalytical rigor and reliability.

  • Proficient time management and prioritization,demonstratedthrough evidence-based examples of organizing work, protecting focus during interruptions, managing competing priorities, and delivering reliably in a fast-moving trading environment.

  • Proficient communication skills, with the ability to explain complex analytical findings clearly, tailor messages to technical and non-technical audiences, andprovideevidence-based examples of effective stakeholder communication.

  • Expert collaboration skills, including acting on feedback, providing constructive feedback to colleagues, sharing knowledge, contributing to collective learning, and constructively handling differences of opinion in ways that strengthen team dynamics.

Preferred:

  • Experience with JIRA, or business intelligence tools such as Tableau is preferred; these skills can be developed on the job where the candidatedemonstratesstrong learning agility.

  • Additionalexperience with APIs, FIX protocol, cloud data platforms, distributed data processing, or market/trading data infrastructure is beneficial.

Trading & Market Knowledge

Proficient knowledge in at least one of the following areas, with competent understanding and genuine interest in developing the others: electronic trading, transaction cost analysis, or financial markets knowledge, particularly fixed income market structure. Candidates should understand how trading workflows, order lifecycle, RFQ protocols, dealer behavior, liquidity formation, best execution, and execution/pricing algorithms connect to practical research and analytics problems.

HOW YOU'LL SUCCEED

Successful candidates are intellectually curious, pragmatic problem-solvers who enjoy working at the intersection of trading, technology, and quantitative research. They take ownership from problem definition through implementation, balancing scientific rigor with practical business impact.They enjoy building production-quality analytical software and understand that elegant research is only valuable when it improves real trading decisions.They are comfortable working with imperfect real-world data, naturally curious about how markets function, and motivated by improving trading outcomes through research, analytics, and innovation.

They thrive in collaborative environments where success depends on partnering effectively with traders, portfolio managers, technologists, and external market participants to transform quantitative insights into better investment decisions.

WHY THIS ROLE IS UNIQUE

This roleprovidesthe opportunity to help shape the future of trading at one of the world's largest institutional asset managers.

Rather than focusing solely on reporting historical performance, you will help developthe predictiveanalytics, systematic trading capabilities, and decision-support tools that define the next generation of portfolio implementation.

You will work directly alongside traders, portfolio managers, technologists, and quantitative researchers to improve execution quality across global fixed income markets and contribute to a platform that continues to evolve through data, research, and innovation.

Not sure you meet 100% of our qualifications? That's ok. If you believe that you could excel in this role, we encourage you to apply and welcome a chance to review your background. We are dedicated to building and maintaining a diversified workforce and considering a broad array of candidates with a variety of skill, workplace experiences, and backgrounds.

As an equal opportunity employer, Wellington Management ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, sex, sexual orientation, gender identity, gender expression, religion, creed, national origin, age, ancestry, disability (physical or mental), medical condition, citizenship, marital status, pregnancy, veteran or military status, genetic information or any other characteristic protected by applicable law. If you are a candidate with a disability, or are assisting a candidate with a disability, and require an accommodation to apply for one of our jobs, please email us at GMWTalentOperations@wellington.com.

At Wellington Management, our approach to compensation is designed to help us attract, inspire and retain the best talent in our industry.We strive to pay employees fairly and competitively across all levels and roles. Our approach to compensation considers all aspects of total compensation; all employees are eligible to receive salary, variable compensation, and benefits. The base salary range for this position is:

USD 90,000 - 180,000

This range takes into account the wide range of factors that are considered when making compensation decisions, including but not limited to skill sets; role; skills and experience; certifications; and education. This range is an estimate, and further details on salary and total compensation aspects will be shared with candidates during the recruitment process.

Base salaryis only one component of Wellington's total compensation approach. Other rewards may include a discretionary Corporate Bonus and/ or Incentives, if eligible. In addition, we offer a comprehensive and high value benefit package to meet the unique needs of our employees and their families, and we are committed to fostering a flexible work environment that enables employees to thrive personally and professionally. Examples of our benefits include retirement plan, health and wellbeing, dental, vision, and pharmacy coverage, health savings account, flexible spending accounts and commuter program, employee assistance program, life and disability insurance, adoption assistance, back-up childcare, tuitio...

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