Minimum of three (3) years' experience in customer analytics domain and/or credit risk assessment ... Bachelor's Degree in quantitative discipline such as Statistics, mathematics, Operations Research ...
Minimum of three (3) years' experience in customer analytics domain and/or credit risk assessment ... Bachelor's Degree in quantitative discipline such as Statistics, mathematics, Operations Research ...
... control, risk management, and performance monitoring. Working closely with the Project Manager ... Perform qualitative and quantitative data gathering and analysis independently. • Coordination ...
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... control, risk management, and performance monitoring. Working closely with the Project Manager ... Perform qualitative and quantitative data gathering and analysis independently. • Coordination ...
Quantitative Risk Manager information
See Miami, AZ salary details
$49.8K - $60.2K
4% of jobs
$60.2K - $70.6K
6% of jobs
$70.6K - $81K
11% of jobs
$84.9K is the 25th percentile. Wages below this are outliers.
$81K - $91.4K
11% of jobs
The median wage is $99.7K / yr.
$91.4K - $101.8K
23% of jobs
$101.8K - $112.2K
13% of jobs
$119.1K is the 75th percentile. Wages above this are outliers.
$112.2K - $122.7K
12% of jobs
$122.7K - $133.1K
8% of jobs
$133.1K - $143.5K
6% of jobs
$143.5K - $153.9K
4% of jobs
$153.9K - $164.3K
2% of jobs
$49.8K
$107.8K
$164.3K
How much do quantitative risk manager jobs pay per year?
As of Jun 28, 2026, the average yearly pay for quantitative risk manager in Miami, AZ is $107,820.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,000.00 and $124,700.00 per year, depending on experience, location, and employer.
Is quantitative risk management in demand?
Quantitative risk management is in high demand across financial services, insurance, and investment firms due to increasing regulatory requirements and the need for sophisticated risk assessment tools. Professionals in this field with skills in data analysis, statistical modeling, and programming are sought after, especially those with certifications like FRM or CFA. The role often involves using software such as Python, R, or MATLAB to develop risk models and monitor financial exposures.
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.
What is the salary of quant Risk Manager?
The salary of a Quantitative Risk Manager typically ranges from $100,000 to $200,000 annually, depending on experience, location, and the size of the organization. Senior roles or those in major financial hubs can earn higher compensation, often including bonuses and performance incentives.
How much do quant risk managers make?
Quantitative risk managers typically earn a median salary ranging from $100,000 to $150,000 annually, with experienced professionals in major financial centers earning over $200,000. Compensation often includes bonuses and depends on factors such as experience, education, certifications, and the complexity of the risk models managed.
What is a quantitative Risk Manager?
A quantitative risk manager is a professional who uses mathematical models, statistical analysis, and programming skills to identify, assess, and mitigate financial risks within an organization. They often work with tools like Excel, R, or Python and require strong knowledge of finance, mathematics, and risk management frameworks. Their goal is to help firms make data-driven decisions to minimize potential losses and ensure regulatory compliance.
What is the difference between Quantitative Risk Manager vs Quantitative Analyst?
| Aspect | Quantitative Risk Manager | Quantitative Analyst |
|---|---|---|
| Primary Focus | Assessing and managing risk exposure across financial portfolios | Developing models and algorithms for investment strategies |
| Required Credentials | Advanced degrees in finance, mathematics, or related fields; certifications like FRM or CFA | Degrees in finance, mathematics, or statistics; often pursuing CFA or similar |
| Work Environment | Financial institutions, risk management departments | Investment firms, hedge funds, banks |
| Key Skills | Risk assessment, regulatory knowledge, quantitative modeling | Data 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 cities near Miami, AZ are hiring for Quantitative Risk Manager jobs? Cities near Miami, AZ with the most Quantitative Risk Manager job openings:
Full-time
Posted 16 days ago
Job description
At Globe, our goal is to create a wonderful world for our people, business, and nation. By uniting people of passion who believe they can make a difference, we are confident that we can achieve this goal.
Job Description The Model Development Manager is responsible for managing analytics projects from development to operationalization, performing analysis and predictive modelling and helping drive the change management process. Responsible for ensuring machine learning jobs are running in production and provide integration to existing and new systems.DUTIES AND RESPONSIBILITIES:Data Management and Exploration
Extraction, exploration and manipulation of large and complex data sets
Designing and derivation of transformed variables for predictive modeling/advanced analytics
Develop big data framework combining telco data with various external sources of data (digital, social, etc) to get a 360-degree view of the customer
Help internal stakeholders in understanding, interpreting and analyzing massive data sets
Data Analytics and Modeling:
Understand and translate business problems into data science projects.
Perform data modeling and create sophisticated analytics models. Implement and test data modeling designs. Use advanced math and statistics expertise using massive (beyond 500GB) data. Use modern data analytical techniques working with information retrieval, machine learning, matrix and graph algorithms, unsupervised clustering & data mining to solve business problems
Track model accuracy and effectiveness
Identify model fine-tuning needs; Measure ROI from models developed
Campaign Expertise
Translate model into results. Draws out and communicates useful insights, actionable interpretations, alternative approaches and solutions.
Identify opportunities for the application of customer analytics techniques for the business, particularly for credit scoring.
Use learnings from models to prioritize and sequence initiatives; Collaborate with business sponsors and different stakeholders to operationalize analytic findings.
Knowledge Transfer and Collaboration
Support internal stakeholders in use of data and various analytical tools to generate and communicate insights
Provides training, demonstration, documentation and other support to drive the change management process and expand the use of analytics throughout the organization
Support the drive for change management process to ensure the analytical developments are adopted by relevant internal teams.
Develop relationships with external data and analytics partners and interact as needed.
Keep updated with new data science techniques and be extremely knowledgeable of industry standards and trends.
REQUIREMENTS:
Minimum of three (3) years' experience in customer analytics domain and/or credit risk assessment and financial services, covering most of the following: data mining, predictive modeling, machine learning, statistical modeling and analysis, large scale data acquisition, transformation, and cleaning, both structured and unstructured data
Proven track record of leading and collaborating on advanced analytics strategic initiatives; Proven track record of operationalization of analytic models in collaboration with marketing/risk and IT teams
Worked with large, unfiltered data sets or data science research
Has Knowledge of both structured and unstructured data
Must possess core competencies, deep understanding and relevant experience in a. Scripting or programming experience: familiarity in programming languages with relational databases (e.g. Python, Java, Ruby, Clojure, Matlab, Pig, SQL)
Statistical Analysis: advanced usage of off-the-shelf tools such as R, SAS, SPSS, Weka and other analytical tools or software
Big Data: Experience with Big data tools such as HDFS, Cassandra, Storm
Database knowledge: skilled in structured database
Familiar with most of the following disciplines:Conceptual modeling: to be able to share and articulate modeling;Predictive modeling: most of the big data problems are towards being able to predict future outcomes;Hypothesis testing: being able to develop hypothesis and test them with carefulexperiments;Natural Language Processing: the interactions between computer and humans;Machine learning: using computers to improve as well as develop algorithms;Statistical analysis: to understand and work around possible limitations in models.
Bachelor's Degree in quantitative discipline such as Statistics, mathematics, Operations Research, Engineering, Computer Science, Econometrics or Information Science such as Business Analytics or Informatics
Equal Opportunity Employer
Globe's hiring process promotes equal opportunity to applicants, Any form of discrimination is not tolerated throughout the entire employee lifecycle, including the hiring process such as in posting vacancies, selecting, and interviewing applicants.
Globe's Diversity, Equity and Inclusion Policy Commitment can be accessed here
Make Your Passion Part of Your Profession. Attracting the best and brightest Talents is pivotal to our success. If you are ready to share our purpose of Creating a Globe of Good, explore opportunities with us.