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Model Risk Manager Jobs in Rhode Island (NOW HIRING)

Citizens Bank

Fraud Risk Analytics Manager

Johnston, RI · On-site

$105K - $130K/yr

... risk management, and product experiences. The ideal candidate brings deep fraud domain expertise ... Model evaluation and performance monitoring Preferred Qualifications * Experience with fraud ...

Citizens

Fraud Risk Analytics Manager

Johnston, RI · Hybrid

$105K - $130K/yr

... risk management, and product experiences. The ideal candidate brings deep fraud domain expertise ... Model evaluation and performance monitoring Preferred Qualifications * Experience with fraud ...

Citizens

Fraud Risk Analytics Manager

Johnston, RI · Hybrid

$105K - $130K/yr

... risk management, and product experiences. The ideal candidate brings deep fraud domain expertise ... Model evaluation and performance monitoring Preferred Qualifications * Experience with fraud ...

Citizens

Fraud Risk Analytics Manager

Johnston, RI · Hybrid

$105K - $130K/yr

... risk management, and product experiences. The ideal candidate brings deep fraud domain expertise ... Model evaluation and performance monitoring Preferred Qualifications * Experience with fraud ...

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Model Risk Manager information

See Rhode Island salary details

$50.4K

$109.2K

$166.5K

How much do model risk manager jobs pay per year?

As of May 30, 2026, the average yearly pay for model risk manager in Rhode Island is $109,248.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,100.00 and $126,300.00 per year, depending on experience, location, and employer.

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

To thrive as a Model Risk Manager, you need a solid background in quantitative finance, statistics, or mathematics, often supported by an advanced degree and experience in model development or validation. Familiarity with programming languages such as Python or R, risk management frameworks, and regulatory requirements like SR 11-7 or ECB guidelines is typically expected. Strong analytical thinking, attention to detail, and effective communication are crucial soft skills for articulating complex model risks to stakeholders. These competencies are vital for ensuring the accuracy, compliance, and reliability of financial models within an organization.

What are some common challenges a Model Risk Manager faces when validating complex financial models?

Model Risk Managers often encounter challenges such as limited or incomplete data, evolving regulatory requirements, and the need to validate highly complex or proprietary models. They must work closely with model developers, quantitative analysts, and compliance teams to ensure all assumptions and methodologies are sound. Staying up to date with industry best practices and maintaining clear documentation are also crucial, as is effectively communicating findings to both technical and non-technical stakeholders.

What does a Model Risk Manager do?

A Model Risk Manager is responsible for identifying, assessing, and mitigating risks associated with financial and analytical models used by an organization. They ensure that models are accurate, reliable, and compliant with regulatory standards by overseeing validation processes and monitoring model performance. Their role often includes collaborating with model developers, conducting independent reviews, and implementing model governance frameworks to minimize potential losses or errors stemming from model misuse or inaccuracies.

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

AspectModel Risk ManagerQuantitative Analyst
Required CredentialsAdvanced degrees in finance, statistics, or mathematics; certifications like FRM or CFADegree in finance, economics, mathematics, or related fields; often CFA or CQF
Work EnvironmentFocus on risk management teams within financial institutions; regulatory complianceAnalytical roles within trading, investment, or banking divisions; model development
Employer & Industry UsageFinancial institutions, banks, asset managersInvestment firms, hedge funds, banks, financial services

The Model Risk Manager primarily oversees and mitigates risks associated with financial models, ensuring compliance and accuracy. In contrast, Quantitative Analysts develop and implement models to support trading, investment, or risk strategies. While both roles require strong quantitative skills and similar credentials, their focus areas differ—risk management versus model development and analysis.

What job categories do people searching Model Risk Manager jobs in Rhode Island look for? The top searched job categories for Model Risk Manager jobs in Rhode Island are:
What cities in Rhode Island are hiring for Model Risk Manager jobs? Cities in Rhode Island with the most Model Risk Manager job openings:
Model Risk Manager jobs near you
Fraud Risk Analytics Manager

Fraud Risk Analytics Manager

Citizens Bank

Johnston, RI • On-site

$105K - $130K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 3 days ago

Job description

Job Description
We are seeking an experienced Senior Data Scientist to lead fraud risk strategy optimization and entity-level fraud state estimation across the enterprise. This role is critical to developing a holistic understanding of customer behavior and translating that understanding into intelligent decisioning and colleague decision support across fraud prevention, risk management, and product experiences.
The ideal candidate brings deep fraud domain expertise spanning across the entire customer life cycle, strong analytical rigor, and the courage to challenge existing approaches while delivering practical, scalable solutions under time constraints and scope changes. This individual will partner closely with business leaders, first- and second-line risk teams, fraud operations, and product to drive measurable fraud risk reduction and improved customer outcomes.
Key Responsibilities
  • Discover, Design, develop, and execute fraud risk strategy optimization frameworks, including rule, model, and hybrid decisioning approaches
  • Perform entity-level fraud state estimation across customers, accounts, devices, and networks to enable consistent, enterprise-wide fraud understanding
  • Translate complex fraud signals into actionable insights and decision support for colleagues across business, risk, and operations
  • Partner with first- and second-line risk teams to ensure strategies are transparent, explainable, and well-governed
  • Collaborate with operations and product teams to ensure well-defined objective functions which are operationally viable and aligned with customer experience goals
  • Communicate findings clearly to both technical and non-technical audiences, influencing decision-making at multiple levels
  • Champion innovation by testing new analytical approaches while maintaining disciplined execution and production readiness

Required Qualifications
  • 5+ years of experience in fraud analytics, fraud risk management, or financial crime data science
  • Strong experience with fraud detection, prevention, and decisioning systems in complex environments
  • Demonstrated ability to balance risk reduction, customer experience, and operational efficiency
  • Proven track record of independent problem-solving, ownership, and delivery in ambiguous problem spaces
  • Excellent communications (oral and written), interpersonal/business partnering, and organizational skills
  • Demonstrates courage, innovation, and high productivity

Technical Skills
  • Advanced SQL for data extraction, transformation, and analysis
  • Strong Python skills for data analysis, modeling, and pipeline development
  • Solid foundation in data science and statistical learning, including:
    • Classification and regression techniques
    • Feature engineering
    • Model evaluation and performance monitoring

Preferred Qualifications
  • Experience with fraud strategy optimization, challenger testing, or decision policy design
  • Familiarity with entity resolution, graph/network analytics, or customer-centric risk frameworks
  • Experience operating within regulated environments and risk governance structures
  • Bachelor's degree in Operations Management, Mathematics, Statistics, Actuarial Sciences, Economics or other quantitative, business or technical discipline
  • Master degree in Mathematics, Statistics, Operations Management, Economics or other quantitative, business or technical discipline preferred

Hours & Work Schedule
  • Hours per Week: 40
  • Work Schedule: 8:00am-5:00pm Monday - Friday

Pay Transparency
The salary range for this position is $105,000 - $130,000 per year. Actual pay is based on various factors including but not limited to the work location, and relevant skills and experience. We offer competitive pay, comprehensive medical, dental and vision coverage, retirement benefits, maternity/paternity leave, flexible work arrangements, education reimbursement, wellness programs and more. Note, Citizens' paid time off policy exceeds the mandatory, paid sick or paid time-away policy of every local and state jurisdiction in the United States. For an overview of our benefits, visit https://jobs.citizensbank.com/benefits
About Us
Equal Employment Opportunity
Citizens, its parent, subsidiaries, and related companies (Citizens) provide equal employment and advancement opportunities to all colleagues and applicants for employment without regard to age, ancestry, color, citizenship, physical or mental disability, perceived disability or history or record of a disability, ethnicity, gender, gender identity or expression, genetic information, genetic characteristic, marital or domestic partner status, victim of domestic violence, family status/parenthood, medical condition, military or veteran status, national origin, pregnancy/childbirth/lactation, colleague's or a dependent's reproductive health decision making, race, religion, sex, sexual orientation, or any other category protected by federal, state and/or local laws. At Citizens, we are committed to fostering an inclusive culture that enables all colleagues to bring their best selves to work every day and everyone is expected to be treated with respect and professionalism. Employment decisions are based solely on merit, qualifications, performance and capability.
Equal Employment and Opportunity Employer
Job Applicant Data Privacy Policy
Background Check
Any offer of employment is conditioned upon the candidate successfully passing a background check, which may include initial credit, motor vehicle record, public record, prior employment verification, and criminal background checks. Results of the background check are individually reviewed based upon legal requirements imposed by our regulators and with consideration of the nature and gravity of the background history and the job offered. Any offer of employment will include further information.

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