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Model Risk Analyst Jobs in Massachusetts (NOW HIRING)

Whoop

AI Risk & Compliance Analyst

Boston, MA · On-site

WHOOP is seeking a Governance, Risk, and Compliance Analyst II, to lead the day-to-day operation ... Experience translating AI-specific risks (i.e., data poisoning, prompt injection, model misuse ...

State Street Global Advisors

Market Risk

Boston, MA · On-site +1

$82K - $180K/yr

... analyzing and continuously enhancing market risk models (VaR, Expected Shortfall, PV01, Option Greeks); performing stress testing, identify portfolio vulnerabilities and support the stress testing ...

State Street Corporation

Market Risk

Boston, MA · On-site

$82K - $180K/yr

... analyzing and continuously enhancing market risk models (VaR, Expected Shortfall, PV01, Option Greeks); performing stress testing, identify portfolio vulnerabilities and support the stress testing ...

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All JobsModel Risk Analyst JobsModel Risk Analyst Jobs in Massachusetts

Model Risk Analyst information

See Massachusetts salary details

$16

$44

$71

How much do model risk analyst jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for model risk analyst in Massachusetts is $44.21, according to ZipRecruiter salary data. Most workers in this role earn between $32.55 and $53.80 per hour, depending on experience, location, and employer.

What is a model risk analyst?

A Model Risk Analyst evaluates, validates, and monitors financial models to ensure they function correctly and comply with regulatory standards. They identify potential risks in model assumptions, data quality, and methodologies. Their work helps financial institutions mitigate model-related risks that could lead to inaccurate decision-making. Analysts collaborate with model developers, risk managers, and auditors to improve model performance and documentation. Strong analytical, statistical, and programming skills are essential for this role.

Do model risk analysts make good money?

Model risk analysts typically earn competitive salaries that vary by industry, experience, and location. Entry-level positions often start around $70,000 annually, with experienced professionals earning over $120,000, especially in financial services and banking sectors. Certifications like CFA or FRM and proficiency in programming tools such as Python or SAS can enhance earning potential.

What skills and qualifications are needed to be a model risk analyst?

To thrive as a Model Risk Analyst, you need strong quantitative analysis skills, a background in mathematics, statistics, finance, or a related field, and experience in model validation practices. Familiarity with programming languages such as Python, R, SAS, and tools like Excel, along with knowledge of regulatory requirements such as SR 11-7, is typically essential; certifications like FRM or CFA can be advantageous. Excellent communication, attention to detail, and critical thinking are important soft skills for presenting findings and collaborating with cross-functional teams. Mastery of these skills ensures the integrity and reliability of risk models, supporting sound business decisions and regulatory compliance.

What does a model risk analyst do?

A model risk analyst evaluates and monitors the risks associated with financial or operational models used by organizations. They review model assumptions, validate model accuracy, and ensure compliance with regulatory standards, often using statistical and analytical tools. Their work helps prevent financial losses and supports decision-making processes.

What challenges might a model risk analyst face in their daily work?

Model Risk Analysts often encounter challenges such as ensuring data quality, identifying model limitations, and keeping up with evolving regulatory standards. They must frequently balance the technical rigor needed to validate complex financial models with the need to communicate their findings clearly to stakeholders without a technical background. Additionally, adapting quickly to new modeling methodologies or changing business priorities is common. Overcoming these challenges requires ongoing learning, strong collaboration with model developers, and a proactive approach to risk management.

What are popular job titles related to Model Risk Analyst jobs in Massachusetts? For Model Risk Analyst jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Model Risk Analyst jobs in Massachusetts look for? The top searched job categories for Model Risk Analyst jobs in Massachusetts are:
Model Risk Analyst jobs near you
Infographic showing various Model Risk Analyst job openings in Massachusetts as of August 2026, with employment types broken down into 2% As Needed, 78% Full Time, 15% Part Time, 1% Temporary, and 4% Contract. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $91,967 per year, or $44.2 per hour.

Senior/Lead Risk Analyst, Payment fraud (Relocation to Toronto Required)

Snaplii

Boston, MA • On-site

$150K - $250K/yr

Full-time

Re-posted 7 days ago

Job description

Lead Risk Analyst, Payment fraud
At Snaplii, risk management isn't a "brake" on growth-it's the "supercharger" that enables our 300% explosive expansion. We aren't looking for analysts who just read reports; we want strategists who can reverse-engineer fraud loops and command AI to automatically sever risks.
Important: Location & Relocation
This role is based in our Toronto, Canada office. To foster our high-velocity founding culture, we require this leader to be onsite in Toronto for at least the first 6-12 months. We provide full relocation assistance and comprehensive immigration sponsorship for qualified US-based candidates.
About Snaplii
Snaplii is one of Canada's fastest-growing fintech platforms, with $100M+ in annual transaction volume and 350,000+ users across North America, Snaplii connects consumers with 500+ leading brands across everyday categories - enabling smarter spending with instant savings and rewards.
Today, Snaplii is evolving beyond a digital wallet into infrastructure for AI-native commerce - enabling secure, programmable transactions between users, brands, and AI agents.
AI drives demand. Snaplii executes the transaction.
About the Role
We are looking for a Risk Leader with deep fraud expertise and raw analytical horsepower. This role will shape and implement cutting-edge risk strategies that drive sustainable growth, minimize losses, and enhance the customer experience. The ideal candidate has direct experience in payment fraud detection and prevention, with the ability to spot fraudulent transactions and translate fraud patterns into scalable, data-driven solutions. This role requires a balance of hands-on fraud investigation, SQL-driven analytics, and collaboration with product and engineering teams to design and implement automated fraud controls.
Key Responsibilities
  • Lead the end-to-end development and execution of financial risk strategies-from opportunity identification to design, testing, launch, and post-production performance monitoring.
  • Identify, investigate and monitor fraudulent or anomalous activity, including isolating and quantifying specific trends driving changes to fraud and payment patterns.
  • Analyze internal and external data and produce authoritative reports and root-cause analysis on fraudulent activities and chargebacks.
  • Experienced in collaborating with engineers and product managers to successfully deploy fraud prevention solutions that balance growth with risk control.
  • Act as a liaison between the company and payment processors/vendors, with strong communication skills to speak the industry language, manage vendor relationships, and ensure effective alignment on fraud and risk management.

Qualifications
  • The ideal candidate is an accountable and resilient team-player who brings a combination of business instincts, technical skills and raw analytical horsepower necessary to support the rapid growth of Snaplli's business.
  • Minimum 5 years of professional work experience; Minimum 3 years in a fraud-related role; Minimum 1 year in the payments industry.
  • Experience working with various payment methods in multi-currency environments, ideally within e-commerce or related industries.
  • Proven ability to investigate and identify fraudulent activities, including hands-on experience with transaction reviews and fraud case analysis.
  • Strong data modeling skills (3+ years): hands-on experience building fraud detection models, user behaviour scoring systems, and transaction anomaly detection models, including feature engineering, model training, evaluation, and deployment.
  • Ability to integrate models with risk systems to enable automated, model-driven fraud prevention workflows.
  • Proficiency with machine learning frameworks (Python or R with Sklearn, XGBoost, LightGBM, etc.) and prior experience deploying models into production environments.
  • SQL proficiency (must-have) - able to independently query and analyze large datasets. Python (good-to-have).
  • Previous experience as a Fraud Analyst, Risk Analyst, Operations Specialist, Data Scientist, or Product Manager. Bachelor's degree in Engineering, Computer Science, Statistics, Finance, or a related analytical/technical field.
  • Strong problem-solving skills and reverse-engineering thinking, with the ability to anticipate and predict potential risks from a fraudster's perspective.
  • Proficiency in Mandarin Chinese is an asset but not required.
Why Join Us
  • Building AI-Native Payments
    • Powering how AI agents transact in the real world.
  • Explosive Growth
    • 300%+ revenue & TPV growth in 2025, with accelerating momentum into 2026.
  • Small Team, Massive Scale
    • <40 people. A lean & high-performance team where every decision moves revenue, risk, and user experience.
  • AI-First Engineering Culture
    • 90%+ of code is AI-assisted. Engineers focus on architecture and complex problems
  • Direct Access to the AI Frontier
    • Connect with leading AI companies in Silicon Valley, gaining first-hand exposure to cutting-edge advancements.

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