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Model Risk Manager Jobs in Raceland, LA (NOW HIRING)

The work model for the role is: Remote {#LI-Remote} This role is contributing to the Country Trade ... Regulatory Compliance & Risk Management * Identify, assess, and mitigate trade compliance risks ...

Culture Champion - Models the Walmart values to foster our culture; holds oneself and others ... and intelligent risk-taking; andexhibitsresilience in the face of setbacks. * Digital ...

Model Risk Manager information

See Raceland, LA salary details

$49.1K

$106.4K

$162.2K

How much do model risk manager jobs pay per year?

As of Sep 5, 2026, the average yearly pay for model risk manager in Raceland, LA is $106,415.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,900.00 and $123,100.00 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 cities near Raceland, LA are hiring for Model Risk Manager jobs?

Cities near Raceland, LA with the most Model Risk Manager job openings:

Infographic showing various Model Risk Manager job openings in Raceland, LA as of June 2026, with employment types broken down into 1% As Needed, 87% Full Time, 9% Part Time, and 3% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $106,415 per year, or $51.2 per hour.

Senior Manager Data Science & AI

Bollinger Shipyards

Raceland, LA • Remote

Full-time

Re-posted 6 days ago


Bollinger Shipyards rating

6.5

Company rating: 6.5 out of 10

Based on 10 frontline employees who took The Breakroom Quiz


Job description

Job Title: Senior Manager Data Science & AI

Location: Remote USA

Position Overview: The Senior Manager, Data Science & AI is responsible for establishing and scaling enterprise artificial intelligence, machine learning, and advanced analytics capabilities across Bollinger Shipyards. This role leads the identification, prioritization, development, and operationalization of AI solutions that improve forecasting, bidding, operational efficiency, planning, and decision-making.

The role partners closely with business leaders, Data Engineering, Analytics, and Enterprise Architecture to ensure AI initiatives are aligned to strategic priorities and successfully integrated into enterprise operations.

Key Responsibilities:

  • ·         Define and execute the enterprise roadmap for AI, machine learning, and advanced analytics initiatives
  • ·         Identify and prioritize high-value AI and predictive analytics use cases aligned to operational and strategic objectives
  • ·         Lead development of models supporting forecasting, cost estimation, scheduling, bidding optimization, operational efficiency, and intelligent automation
  • ·         Establish standards and governance for model development, validation, deployment, monitoring, and lifecycle management
  • ·         Ensure AI and ML solutions are integrated into enterprise workflows and production systems
  • ·         Partner with Data Engineering teams to ensure availability of scalable, high-quality datasets for model development
  • ·         Collaborate with business leaders to drive adoption and measurable business value from AI capabilities
  • ·         Evaluate emerging AI technologies, platforms, and opportunities relevant to Bollinger’s operational environment
  • ·         Lead and develop data science and ML engineering resources
  • ·         Ensure responsible, secure, and compliant use of AI technologies and enterprise data
  • ·         Establish KPIs and performance measures for AI initiatives and operational impact

Qualifications:

•           Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, Mathematics, or related field

•           8+ years of experience in data science, AI, machine learning, or advanced analytics roles

•           3+ years of leadership experience

•           Proven experience leading enterprise AI and ML initiatives from concept through operational deployment

•           Strong background in statistical modeling, machine learning, predictive analytics, and optimization techniques

•           Experience working with large and complex enterprise datasets

•           Experience leading technical teams and enterprise-scale initiatives

Skills and Abilities:

•           Experience in manufacturing, industrial, shipbuilding, engineering, or operational environments

•           Experience with Azure AI, ML Ops, cloud AI platforms, and modern AI frameworks

•           Familiarity with Generative AI, intelligent automation, and agent-based AI applications

•           Experience operationalizing AI solutions within ERP or operational systems

•           Knowledge of AI governance, model risk management, and responsible AI practices

Bollinger is an equal opportunity employer and is committed to providing employment opportunities to minorities, females, veterans and disabled individuals, and without regard to sexual orientation and gender identity.


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