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Quantitative Risk Management Jobs (NOW HIRING)

Key Responsibilities: * Assist the Quantitative Risk Manager in constructing a Credit Decision Scorecards and statistically based credit risk modeling strategies based on quantitative modeling ...

As a Quantitative Risk Management Intern within Enterprise Risk Management (ERM), you will apply advanced analytical, technical, and quantitative skills to support risk management activities at one ...

You will manage client data workflows, maintain and troubleshoot Python-based automations, and ... How We Work As a Quantitative Risk Analyst you will be expected to work in a hybrid environment.

You will manage client data workflows, maintain and troubleshoot Python-based automations, and ... How We Work As a Quantitative Risk Analyst you will be expected to work in a hybrid environment.

Quant Risk Analyst

New York, NY · On-site

$100K - $150K/yr

Quantitative risk management background with direct ownership of model development, not just consumption of outputs from a research team. * Strong financial modeling skills in Python. You write clean ...

$200 - $250/hr

Quantitative risk management background with direct ownership of model development, not just consumption of outputs from a research team. * Strong financial modeling skills in Python. You write clean ...

Position Summary As a Quantitative Risk Modeling Led in the Ryan Credit Solutions department at ... We partner with banks, asset managers, and insurers to create bespoke solutions that address ...

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Quantitative Risk Management information

See salary details

$51.5K

$111.6K

$170K

How much do quantitative risk management jobs pay per year?

As of Sep 8, 2026, the average yearly pay for quantitative risk management in the United States is $111,556.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $129,000.00 per year, depending on experience, location, and employer.

What is quantitative risk management?

Quantitative risk management is the process of using mathematical models, statistical techniques, and data analysis to identify, measure, and manage financial risks within an organization. Professionals in this field apply quantitative methods to assess potential losses from market movements, credit events, or operational failures, and help organizations make informed decisions to mitigate these risks. This approach is widely used in banking, insurance, asset management, and other financial sectors to ensure regulatory compliance and optimize risk-adjusted returns.

How does a quantitative risk management professional typically collaborate with other departments within a financial institution?

Quantitative Risk Management professionals frequently work closely with departments such as trading, finance, and compliance. They provide analytical support by developing risk models and stress-testing scenarios, ensuring that trading strategies and investment decisions align with the institution's risk appetite. Regular communication with IT teams is also common, as these professionals often need to implement or improve risk measurement tools and data systems. This cross-functional collaboration is essential for maintaining a robust risk management framework and responding effectively to emerging risks.

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 skills, expertise in statistics or mathematics, and typically a degree in finance, economics, or a quantitative discipline. Familiarity with risk modeling software, programming languages like Python or R, and industry certifications such as FRM or CFA is often required. Outstanding problem-solving abilities, attention to detail, and effective communication set top professionals apart in this role. These skills are crucial for accurately assessing financial risks, making informed decisions, and communicating complex findings to stakeholders.

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

AspectQuantitative Risk ManagementQuantitative Analyst
Primary FocusAssessing and managing financial risksDeveloping models for investment strategies
CertificationsFRM, PRMCFA, CQF
Work EnvironmentFinancial institutions, risk departmentsInvestment banks, asset management firms
Key SkillsRisk modeling, regulatory knowledgeStatistical analysis, programming

Quantitative Risk Management focuses on identifying and mitigating financial risks within organizations, often requiring risk-specific certifications like FRM. In contrast, Quantitative Analysts develop models to support trading and investment decisions, emphasizing statistical and programming skills. Both roles are vital in finance but serve different strategic purposes.

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 financial analyst in banking, insurance, or investment firms. These roles involve assessing and mitigating financial risks using statistical models, data analysis, and tools like Excel, R, or Python. Certification programs like FRM or PRM can enhance career prospects.

What does a quantitative risk management do?

A quantitative risk management professional analyzes financial data and models to identify, measure, and mitigate potential risks to an organization. They use statistical tools, programming skills, and risk assessment techniques to develop strategies that minimize losses and ensure regulatory compliance.
More about Quantitative Risk Management jobs

What cities are hiring for Quantitative Risk Management jobs?

Cities with the most Quantitative Risk Management job openings:

What states have the most Quantitative Risk Management jobs?

States with the most job openings for Quantitative Risk Management jobs include:

Infographic showing various Quantitative Risk Management job openings in the United States as of September 2026, with employment types broken down into 8% Internship, 76% Full Time, 8% Temporary, and 8% Contract. Highlights an 75% In-person, 8% Hybrid, and 17% Remote job distribution, with an average salary of $111,556 per year, or $53.6 per hour.

Quantitative Risk Analyst

WSFS Bank

Philadelphia, PA

$64K - $105K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 2 days ago


WSFS Bank rating

7.2

Company rating: 7.2 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

118th of 176 rated banks


Job description

Job Description

NewLane Finance is seeking an individual to assist the credit and risk modeling and analytics function using data to advance credit risk behavior and quantification of these risk and return tradeoffs through the deployment of models and algorithms to optimize such strategies. This role will be responsible for providing analytical/quantitative input to help develop, implement, and monitor the build of complex commercial small business Expected Default (ED) and Probability of Default (PD) credit default models.

The successful candidate will use their business analysis, process, and quantitative knowledge to ensure business intent is matched with modeling outcome, and document development decisions under SR117 guidelines. In addition to responsibilities on individual modeling projects this role will be expected to work on adhoc projects as needed. Communicating model mechanics and articulating nuances to leadership will be an important aspect of the role. This is a great opportunity for someone who is a modeler/statistician/data analyst/coder (or a combination) with experience in commercial small business credit analysis.

Key Responsibilities:

  • Assist the Quantitative Risk Manager in constructing a Credit Decision Scorecards and statistically based credit risk modeling strategies based on quantitative modeling methods (e.g., good / bad definition, performance sample windows, sample size and exclusions).
  • Assist in developing and implementing a framework for data collection, processing and analyzing customer and 3rd party data (e.g., PayNet, D&B, consumer credit bureaus) for implementing credit risk strategies
  • Plan and execute self-driven analytics on large data sets (structured and unstructured data) using next generation technologies, prepare analysis and reports to support discussions on key analytics and model aspects to drive decision making
  • Validate credit default rates from portfolio attributes (e.g., delinquencies, EOD, loss curves, dealer performance) and make recommendations on credit model and policies
  • Work with sales management on risk-based pricing strategies optimizing dealer conversion rates and profitability.
  • Oversight of credit data mart used for reporting and portfolio performance monitoring.
  • Supporting ongoing and future projects working with the senior team.
  • Ability to create visualizations of data and/or quantitative information for management decision-making
  • Support building and enhancing procedures and model documentation in compliance with regulatory guidance as well as the Bank's model risk policy
  • Maintain current/develop new analytical reports and presentations for senior management, executive committees, and regulatory exams

Experience:

  • Bachelor's degree in Mathematics/Statistics, Operations Research, Economics, Finance, or other quantitative discipline; or in lieu of a degree, four (4) plus years' experience in Risk, Finance, Consumer Lending
  • Three (3) plus years of commercial small business credit modeling experience.
  • Two (2) plus years of experience in Consumer Lending statistical modeling/analytics, preferably related to ALL and/or Loss Forecasting modeling for credit cards.
  • Two (2) plus years in coding with Python, PySpark or other equivalent language within the past Five (5) years

Desired Characteristics:

  • Demonstrated experience with SAS and other statistical methods.
  • Proven decision-making role constructing credit models in a regulated environment
  • Strong quantitative and analytical skills in statistical analysis and data science best practices
  • Strong communication and partnering skills

Salary Range:

$64,491.00 - $105,949.50

Individual base pay may vary on additional factors such as the candidate's experience, job-related skills, relevant education, geographic location, and other specific business and organizational needs.

In addition to base salary, WSFS Financial Corporation (WSFS) and its subsidiaries may offer eligible Associates discretionary and formula-based incentive and retention awards. WSFS provides a competitive benefits package, which includes medical, dental, and vision coverage; a 401(k) plan; life, accident, and disability insurance; flexible spending accounts (FSAs) and health savings accounts (HSAs); and wellness programs. Additional benefits may include paid parental leave, military leave, vacation and other paid time off, sick leave in accordance with applicable state laws, and paid holidays. Benefit offerings are subject to eligibility requirements, legal limitations, and may vary based on an Associate's location and employment status. For more information about Associate benefits, please visit https://www.wsfsbank.com/about/careers/

WSFS Bank is inclusive and supportive of individual needs. If you have a physical or other impairment that might require an accommodation, including technical assistance with the WSFS Bank Careers website or submission process, please contact us via email at careers@wsfsbank.com.

WSFS is an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.


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