ZipRecruiter

Log In

1

Quantitative Risk Analyst Jobs in New Jersey (NOW HIRING)

Amicis Global

Quantitative Analyst

Jersey City, NJ · On-site

$75 - $85/hr

Quantitative Analyst Duration: 6+ Months Location: Jersey City, NJ, 07311 Summary ... The Insider Risk team, in partnership with the Information Security Data Operations team, is ...

3M HEALTHCARE

Senior Financial Risk Analyst

Edison, NJ · On-site

$111K - $130K/yr

... quantitative analyses into liquidity risks emerging across the Robinhood ecosystem Enhance and ... risk models and forecasting frameworks to support proactive risk management Partner with Data ...

3M HEALTHCARE

Senior Financial Risk Analyst

Edison, NJ · On-site

$111K - $130K/yr

... quantitative analyses into liquidity risks emerging across the Robinhood ecosystem Enhance and ... risk models and forecasting frameworks to support proactive risk management Partner with Data ...

StradIT

Quantitative Analyst

Jersey City, NJ

Maintain and enhance in-house fixed income risk models Design and produce model performance metrics ... validate analysis results to ensure quality Requirements Qualifications: 5+ years of working ...

StradIT

Quantitative Analyst

Jersey City, NJ · On-site

Primary Responsibilities: • Maintain and enhance in-house fixed income risk models • Design and ... • Independently format and validate analysis results to ensure quality Requirements ...

previous pagenext page

Showing results 21-40

All JobsQuantitative Risk Analyst JobsQuantitative Risk Analyst Jobs in New Jersey

Quantitative Risk Analyst information

See New Jersey salary details

$57.4K

$135.9K

$243.7K

How much do quantitative risk analyst jobs pay per year?

As of Aug 8, 2026, the average yearly pay for quantitative risk analyst in New Jersey is $135,917.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,200.00 and $147,700.00 per year, depending on experience, location, and employer.

What are some common challenges a quantitative risk analyst faces when integrating new data sources into risk models?

Quantitative Risk Analysts often encounter challenges related to data quality, consistency, and compatibility when integrating new data sources into risk models. Ensuring that the data is accurate, timely, and relevant requires rigorous validation and sometimes complex data cleaning processes. Additionally, analysts must adapt existing risk models to accommodate new variables, which may involve re-calibrating parameters or even restructuring parts of the model. Effective collaboration with IT and data engineering teams is essential to streamline data integration and maintain model reliability.

What are the key skills and qualifications needed to thrive as a quantitative risk analyst?

To thrive as a Quantitative Risk Analyst, you need strong analytical and mathematical skills, experience with statistical modeling, and typically a degree in finance, mathematics, statistics, or a related field. Proficiency in programming languages such as Python, R, or MATLAB, and familiarity with risk management systems and financial databases are important technical requirements. Attention to detail, problem-solving abilities, and effective communication are vital soft skills for explaining complex analyses to stakeholders. These skills are crucial for accurately identifying, measuring, and mitigating financial risks in dynamic market environments.

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

AspectQuantitative Risk AnalystCredit Risk Analyst
Required CredentialsDegree in finance, economics, or mathematics; certifications like FRM or CFADegree in finance, economics, or related; certifications like FRM or CFA often preferred
Work EnvironmentFinancial institutions, investment firms, risk management departmentsBanks, lending institutions, credit agencies
Employer & Industry UsageUsed across finance sectors for risk modeling and analysisPrimarily in banking and lending for assessing creditworthiness
Comparison Search IntentUnderstanding differences in risk analysis rolesDistinguishing credit-specific risk roles from broader risk analysis

While both roles involve risk assessment and require similar credentials, a Quantitative Risk Analyst focuses on modeling and analyzing various financial risks using quantitative methods across multiple risk types. In contrast, a Credit Risk Analyst specializes in evaluating creditworthiness and managing credit risk specifically within lending and banking sectors.

What is a quantitative risk analyst?

A Quantitative Risk Analyst is a professional who uses mathematical models, statistical techniques, and data analysis to assess and manage financial risks within an organization. They typically evaluate potential losses from market movements, credit defaults, or operational failures and help develop strategies to mitigate those risks. Their work is crucial in industries such as banking, investment, insurance, and asset management, where understanding and controlling risk is essential for financial stability and compliance. Quantitative Risk Analysts often work with complex financial instruments and large datasets, requiring strong analytical and programming skills.
What are popular job titles related to Quantitative Risk Analyst jobs in New Jersey? For Quantitative Risk Analyst jobs in New Jersey, the most frequently searched job titles are:
What job categories do people searching Quantitative Risk Analyst jobs in New Jersey look for? The top searched job categories for Quantitative Risk Analyst jobs in New Jersey are:
What cities in New Jersey are hiring for Quantitative Risk Analyst jobs? Cities in New Jersey with the most Quantitative Risk Analyst job openings:
Quantitative Risk Analyst jobs near you
Infographic showing various Quantitative Risk Analyst job openings in New Jersey as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 8% Part Time, and 3% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $135,917 per year, or $65.3 per hour.

Quantitative Analyst

Amicis Global

Jersey City, NJ • On-site

$75 - $85/hr

Contractor

Re-posted 20 days ago

Job description

Title: Quantitative Analyst
Duration: 6+ Months
Location: Jersey City, NJ, 07311
 
Summary:
The Insider Risk team, in partnership with the Information Security Data Operations team, is working on a project to centralize IR data in the Cybersecurity Data Lakehouse (CyberDW). We are looking for a Data Scientist who can work with the developers and Data Analysts to perform analytics, develop risk and quant models around Insider Risk data. Ultimately, we want to create a human risk score for the Insider Risk program. This individual will be adept at ML, AI, and best practices around the new tools in the marketplace.
The Data Scientist / Data Modeler / Quantitative Analyst will play a critical role in advancing the Insider Risk program's detection, scoring, and decisioning capabilities. This role is responsible for designing, building, and continuously improving quantitative models, statistical methods, and analytical frameworks used to identify, assess, and prioritize insider risk across employees, contractors, vendors, and non‐human identities.
The role partners closely with Cyber, HR, Legal, Compliance, Anti‐Fraud, and Enterprise Information Protection to transform complex enterprise data into defensible risk signals, transparent scoring models, and executive‐level metrics that support investigations, governance, and regulatory scrutiny.
Required Skills:
1) Bachelor's or Master's degree in Data Science, Statistics, Applied Mathematics, Economics, Quantitative Finance, Computer Science, or a related discipline.
2) 5+ years of experience in data science, quantitative analysis, or risk modeling, preferably in financial services or regulated industries.
3) Strong experience building statistical or machine‐learning models (regression, classification, anomaly detection, clustering).
4) Proficiency in Python and/or R, with experience in SQL for large‐scale data analysis.
5) Hands‐on experience working with complex enterprise datasets and translating analytics into business decisions.
6) Strong communication skills with the ability to explain complex analytical concepts to non‐technical stakeholders.
7) Experience supporting Insider Risk, Fraud, AML, Cybersecurity, UEBA, or Threat Analytics programs.
8) Familiarity with identity and access data, endpoint telemetry, DLP, email, or collaboration monitoring.
9) Experience with model explainability, governance, and validation in regulated environments.
10) Knowledge of employee lifecycle risk, behavioral analytics, or human‐centric risk modeling.