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Model Risk Manager Jobs in Atlanta, GA (NOW HIRING)

Pwc

Data Validation Risk - Manager

Atlanta, GA · On-site

$99K - $232K/yr

... Validation Risk Manager, you will play a pivotal role within our Risk & Regulatory practice ... You will utilize skills in data manipulation, visualization, and statistical modeling to support ...

Ryan Specialty

Catastrophe Risk Analyst

Atlanta, GA · On-site

$72K - $90K/yr

The Catastrophe Risk Analyst analyzes data, models risk and provides strategic recommendations to enhance risk management strategies. What will your job entail? Responsibilities * Conduct detailed ...

Ryan Specialty

Catastrophe Risk Analyst

Atlanta, GA · On-site

$72K - $90K/yr

The Catastrophe Risk Analyst analyzes data, models risk and provides strategic recommendations to enhance risk management strategies. What will your job entail? Responsibilities * Conduct detailed ...

Intuit

Lead, IT SOX Risk Advisory

Atlanta, GA

SRCO is a management-led function purpose-built to deliver a modern, sustainable, and risk-focused ... model tools to analyze PRDs, engineering specs, and system change documentation for ICFR risk ...

Intuit

Lead, IT SOX Risk Advisory

Atlanta, GA

SRCO is a management-led function purpose-built to deliver a modern, sustainable, and risk-focused ... model tools to analyze PRDs, engineering specs, and system change documentation for ICFR risk ...

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Showing results 21-40

All JobsModel Risk JobsModel Risk Manager JobsModel Risk Manager Jobs in Atlanta, GA

Model Risk Manager information

See Atlanta, GA salary details

$49.5K

$107.3K

$163.5K

How much do model risk manager jobs pay per year?

As of Aug 21, 2026, the average yearly pay for model risk manager in Atlanta, GA is $107,279.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,500.00 and $124,100.00 per year, depending on experience, location, and employer.

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 skills and qualifications are needed to be a model risk manager?

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 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 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 are popular job titles related to Model Risk Manager jobs in Atlanta, GA?

For Model Risk Manager jobs in Atlanta, GA, the most frequently searched job titles are:

What job categories do people searching Model Risk Manager jobs in Atlanta, GA look for?

The top searched job categories for Model Risk Manager jobs in Atlanta, GA are:

What cities near Atlanta, GA are hiring for Model Risk Manager jobs?

Cities near Atlanta, GA with the most Model Risk Manager job openings:

Model Risk Manager jobs near you
Infographic showing various Model Risk Manager job openings in Atlanta, GA as of August 2026, with employment types broken down into 86% Full Time, 11% Part Time, and 3% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $107,279 per year, or $51.6 per hour.

Lead Risk Data Scientist & ML Engineer

Worldpay

Atlanta, GA • On-site

Full-time

Re-posted 15 days ago

Job description

Job Description
Ready to take your career global?
Make your mark at one of the biggest names in payments. We are seeking a hands-on Lead Risk Data Scientist & ML Engineer to own the full lifecycle of fraud detection and risk models. This role combines deep data science expertise with practical AI/agentic workflow experience and the infrastructure knowledge needed to ship at scale.
What You'll Own
In this role, you'll own the end-to-end delivery of detection models and AI-assisted workflows that power fraud, credit, and AML risk operations. You'll drive model performance through the full lifecycle, from design and validation through production deployment and continuous optimization. You'll translate regulatory requirements and operational needs into detection strategies and technical execution plans, partner across Risk, Compliance, and Technology to ensure alignment, and lead project teams through complex, ambiguous detection challenges. This is a hands-on role that combines deep technical leadership with pragmatic problem-solving in a small, high-impact team.
Model Development & Deployment (End-to-End)
  • Own the full lifecycle of ML models: design, development, validation, deployment, and serving in production
  • Lead model performance monitoring and continuous refinement using production data and investigation outcomes
  • Ensure models are explainable, auditable, and aligned with regulatory expectations
  • Design and oversee scalable batch and real-time data pipelines supporting model development and serving

AI & Agentic Workflows
  • Design and deploy AI-assisted analyst workflows using LLMs and agentic frameworks
  • Guide the development of agent-based systems that augment human decision-making in risk operations
  • Work at the pilot/proof-of-concept stage, establishing best practices for scale

Detection Strategy & Performance
  • Define and refine detection strategies based on emerging fraud patterns and regulatory requirements
  • Maintain and monitor key performance metrics (precision, recall, false positives, alert quality)
  • Influence tradeoff decisions between detection coverage, operational cost, and false positive rates

Governance & Regulatory Alignment
  • Define governance standards for model development, validation, documentation, and change management
  • Ensure compliance with regulatory expectations (BSA/AML, OFAC, FinCEN, SR 11-7)
  • Partner with Model Risk Management and Compliance to support validation and regulatory reviews

Cross-Functional Partnership
  • Serve as the primary technical partner to Fraud Operations, Compliance, and Technology teams
  • Translate regulatory and operational requirements into technical execution plans
  • Drive alignment across teams to enable effective detection capability implementation

Team Leadership & Project Ownership
  • Lead cross-functional project teams through ML model and AI workflow development, from conception to deployment
  • Establish clear priorities, performance expectations, and delivery accountability for project work
  • Provide technical guidance and mentorship to data scientists and engineers executing on risk initiatives
  • Build and strengthen team capabilities across detection modeling, data engineering, and AI/agentic systems

What you'll bring:
Experience
  • 7+ years in data science, machine learning or MLOps
  • Proven experience developing, deploying, and maintaining detection models (fraud, AML, or credit risk) in production environments
  • Hands-on experience with AI-assisted workflows, LLMs, and agentic frameworks (including pilot-stage deployments)
  • Experience in regulated financial services or fintech environments preferred
  • Exposure to model risk management frameworks (SR 11-7) and regulatory interactions

Technical & Domain Expertise
  • Strong proficiency in Python and SQL
  • MLOps experience: Git, GitHub Actions, CI/CD practices, model monitoring, retraining pipelines, infrastructure automation
  • Hands-on experience with data science platforms (Databricks, Snowflake, AWS SageMaker)
  • AWS ecosystem expertise: SageMaker, Glue, Lambda, EventBridge, and related services
  • Familiarity with LLM and agentic frameworks: foundational models (Claude, GPT, etc.), agent orchestration tools (AWS AgentCore, LangChain, etc.)
  • Understanding of fraud typologies, AML transaction monitoring methodologies, and detection system design

Leadership Profile
  • Resourceful and versatile: thrives in a small, fast-moving team; comfortable wearing multiple hats and delivering with constrained resources
  • Startup mentality: pragmatic problem-solver who ships solutions; bias toward execution and measurable outcomes
  • Combines technical depth with collaborative leadership. Guides project teams through ambiguous problems and drives clarity, structure, and delivery
  • Collaborates effectively across Risk, Compliance, and Technology functions; comfortable operating in ambiguity and translating strategy into action

About the team
Our inclusive and global teams win together every day. We're proud to have the best minds in the industry, who you can learn from as you grow your career. The people, the energy, the connections - it's unmatched. Come and be part of an ever-evolving company and get dynamic opportunities that go beyond borders.
What makes a Globalpayer?
Globalpayers think like a client, act like an owner and win as one team. We're curious and innovative -always finding better ways to deliver impact. We empower each other to make decisions, and it's our passion that drives excellence in everything we set out to do.
#LI-BJ1
EEOC Statement
Worldpay is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics. The EEO is the Law poster is available here.
If you are made a conditional offer of employment and will be working in the United States, you will be required to undergo a drug test. In developing this job description care was taken to include all competencies and requirements needed to successfully perform the position. Reasonable accommodations will be provided for individuals with qualified disabilities both during the hiring process, as well as to allow the individual to perform the essential functions of the job, if hired.

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