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Model Risk Manager Jobs in St Louis, MO (NOW HIRING)

Senior Forward Deployed Engineer- AWS

Saint Louis, MO · On-site

$101K - $139K/yr

... managing expectations, and supporting long-term engagement success. Drive end-to-end sales and ... Apply architecture decisions that balance quality, safety, latency, cost, and model risk. Deliver ...

Lead Technical Program Manager

O Fallon, MO · On-site

$120K - $156K/yr

... model governance, and AI risk management. • Proven success leading complex programs involving distributed systems, data platforms, and AI technologies. • Strong ability to manage dependencies ...

EHS Manager

Saint Louis, MO · On-site

$77K - $105K/yr

Ensure compliance with OSHA Process Safety Management and EPA Risk Management Program guidelines ... Model the Spectrum Brands core values of Trust, Accountability and Collaboration to achieve service ...

... risk monitoring. * Execute against the margin operating model aligned to firm priorities and ... Manage the end-to-end lifecycle of margin calls, including issuance, tracking, and liquidation ...

AI Security Engineer Senior Manager

Saint Louis, MO · On-site

$111K - $152K/yr

Lead AI Risk & Governance Establish frameworks to manage AI-specific risks (e.g., model integrity, data leakage, adversarial threats, misuse). Partner with risk and legal to operationalize ...

... managing delegated authority and program business across multiple lines of business. Our team ... Partner with actuarial and modeling teams to evaluate pricing adequacy and expected performance

... models. In this role, you will: * Serve as the Product Owner for one or more Investment Solutions ... Own backlog management across risk implementation capabilities, ensuring clear requirements ...

Showing results 41-60

Model Risk Manager information

See St Louis, MO salary details

$50.1K

$108.5K

$165.3K

How much do model risk manager jobs pay per year?

As of Jul 29, 2026, the average yearly pay for model risk manager in St Louis, MO is $108,458.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,500.00 and $125,400.00 per year, depending on experience, location, and employer.

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 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 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 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 are popular job titles related to Model Risk Manager jobs in St Louis, MO? For Model Risk Manager jobs in St Louis, MO, the most frequently searched job titles are:
What job categories do people searching Model Risk Manager jobs in St Louis, MO look for? The top searched job categories for Model Risk Manager jobs in St Louis, MO are:
What cities near St Louis, MO are hiring for Model Risk Manager jobs? Cities near St Louis, MO with the most Model Risk Manager job openings:
Infographic showing various Model Risk Manager job openings in St Louis, MO as of July 2026, with employment types broken down into 86% Full Time, 13% Part Time, and 1% Contract. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $108,458 per year, or $52.1 per hour.
Senior Forward Deployed Engineer- AWS

Senior Forward Deployed Engineer- AWS

Deloitte

Saint Louis, MO • On-site

$101K - $139K/yr

Other

Posted 19 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 91 frontline employees who took The Breakroom Quiz

56th of 150 rated financial services


Job description

At Deloitte, Senior Forward Deployed Engineers (SFDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends September 30, 2026

Work you'll do

As a Senior FDE, you will work side by side withseniorfunctional and technicalclientteam membersto rapidly prototype and deliver high-impact GenAI-enabledsolutions.This requiresahighly motivatedpractitioner who moves with speed and precision,building working software, engaging confidently with senior stakeholders and engineers to bringmeasurablebusinessimpactfrom day one. Additional responsibilities include:

Client Engagement

Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.

Partner with leaders, product owners, architects, and engineers to align priorities and delivery.

Lead working sessions to shape solutions and drive client outcomes.

Prototype and deliver working AI solutions using industry expertise and emerging capabilities.

Contribute independently within an FDE pod while mentoring newer team members.

Coach client teams and end users on platform capabilities and AI enablement, while building trusted relationships, managing expectations, and supporting long-term engagement success.

Drive end-to-end sales and delivery support by developing demos/POCs, contributing to proposals and orals, articulating business value, and documenting solutions for smooth client handoff and knowledge transfer.

Strengthen team and organizational impact by mentoring other FDEs through design/code reviews and feedback, while contributing reusable components to intellectual capital.

Solution Engineering

Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.

Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.

Apply architecture decisions that balance quality, safety, latency, cost, and model risk.

Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.

Design extensible functionality, support sprint sizing, and align solutions with senior team members.

Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.

The team

AI & Engineeringleverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications

Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.

5+ yearsof experience in software engineering, data engineering, data science, or analytics engineering.

1+ yearsof hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments

1+ years of experience with AWS AI&Data including hands on experience with one of the following key platforms/products;Amazon Bedrock, Bedrock Agents, Knowledge Bases, Guardrails

1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions

1+ years of experience building reliable, maintainable, and well-documented code

Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve

Limited immigration sponsorship may be available

Preferred qualifications

Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)

Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation

Experience withMLOps/LLMOpspractices: evaluation frameworks, model monitoring, and prompt management

Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures

Experienceoperatingwithin hybrid onshore/offshore teams

Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

At Deloitte, Senior Forward Deployed Engineers (SFDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends September 30, 2026

Work you'll do

As a Senior FDE, you will work side by side withseniorfunctional and technicalclientteam membersto rapidly prototype and deliver high-impact GenAI-enabledsolutions.This requiresahighly motivatedpractitioner who moves with speed and precision,building working software, engaging confidently with senior stakeholders and engineers to bringmeasurablebusinessimpactfrom day one. Additional responsibilities include:

Client Engagement

Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.

Partner with leaders, product owners, architects, and engineers to align priorities and delivery.

Lead working sessions to shape solutions and drive client outcomes.

Prototype and deliver working AI solutions using industry expertise and emerging capabilities.

Contribute independently within an FDE pod while mentoring newer team members.

Coach client teams and end users on platform capabilities and AI enablement, while building trusted relationships, managing expectations, and supporting long-term engagement success.

Drive end-to-end sales and delivery support by developing demos/POCs, contributing to proposals and orals, articulating business value, and documenting solutions for smooth client handoff and knowledge transfer.

Strengthen team and organizational impact by mentoring other FDEs through design/code reviews and feedback, while contributing reusable components to intellectual capital.

Solution Engineering

Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.

Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.

Apply architecture decisions that balance quality, safety, latency, cost, and model risk.

Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.

Design extensible functionality, support sprint sizing, and align solutions with senior team members.

Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.

The team

AI & Engineeringleverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications

Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.

5+ yearsof experience in software engineering, data engineering, data science, or analytics engineering.

1+ yearsof hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments

1+ years of experience with AWS AI&Data including hands on experience with one of the following key platforms/products;Amazon Bedrock, Bedrock Agents, Knowledge Bases, Guardrails

1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions

1+ years of experience building reliable, maintainable, and well-documented code

Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve

Limited immigration sponsorship may be available

Preferred qualifications

Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)

Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation

Experience withMLOps/LLMOpspractices: evaluation frameworks, model monitoring, and prompt management

Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures

Experienceoperatingwithin hybrid onshore/offshore teams

Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Education:Bachelor's DegreeEmployment Type:

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