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Model Risk Jobs in Louisiana (NOW HIRING)

The Program offers students an array of experiences including Life and Annuity Valuation, Modeling and Forecasting, Product Management, Asset Liability Management, and Enterprise Risk Management. The ...

Support threat modeling, risk assessments, and security architecture reviews for applications. Ensure that all security practices meet regulatory and compliance requirements. Develop and deliver ...

... risk protections Financial Stewardship & Budget Governance * Oversee operational budget planning and financial management across Autodesk's strategic events portfolio * Establish forecasting models ...

... value with risk mitigation. Solve complex problems while ensuring protection of data, models, and systems. Hands-On AI Security Engineering Actively contribute to architecture, design, and ...

Model and cascade behaviors supporting BNA capabilities (Operational Excellence, People Management, Business Intelligence, Customer Satisfaction, Value Chain Integration and Risk Management)

Model and cascade behaviors supporting BNA capabilities (Operational Excellence, People Management, Business Intelligence, Customer Satisfaction, Value Chain Integration and Risk Management)

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Model Risk information

What are some typical challenges faced by professionals working in Model Risk, and how can they be addressed?

Professionals in Model Risk often encounter challenges such as ensuring model accuracy, managing regulatory compliance, and effectively communicating complex technical findings to non-technical stakeholders. Addressing these challenges requires a strong understanding of both quantitative modeling and relevant regulations, as well as strong collaboration skills to work with model developers, auditors, and business units. Staying informed about evolving regulatory standards and participating in ongoing training can also help model risk professionals remain effective and add value to their organizations.

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

To thrive as a Model Risk Analyst, you need a solid background in quantitative analysis, statistics, or finance, often supported by an advanced degree in a related field. Familiarity with model validation tools, programming languages such as Python or R, and regulatory frameworks like SR 11-7 is essential. Strong analytical thinking, attention to detail, and effective communication skills are crucial for evaluating models and presenting findings to stakeholders. These skills ensure model integrity, regulatory compliance, and risk mitigation in financial institutions.

What is the difference between Model Risk vs Model Validation?

AspectModel RiskModel Validation
Primary FocusIdentifying, assessing, and mitigating risks associated with modelsEvaluating and testing models to ensure accuracy and reliability
Required CredentialsQuantitative skills, risk management certifications, industry experienceQuantitative expertise, validation certifications, industry knowledge
Work EnvironmentRisk management teams within financial institutions or firmsModel validation teams, often within risk or model development departments
Industry UsageUsed across banking, insurance, and investment firms to manage model-related risksCommonly employed in financial services to verify model performance

Model Risk focuses on managing the potential negative impacts of models, including errors and misuse, while Model Validation concentrates on testing and confirming the accuracy and robustness of models. Both roles are essential in financial industries to ensure models are reliable and risks are minimized.

What is model risk?

Model risk refers to the potential for adverse consequences resulting from decisions based on incorrect or misused models. In financial institutions, model risk can arise if a model's assumptions are flawed, if the data input is poor, or if the model is applied inappropriately. Managing model risk involves validating models, monitoring their performance, and ensuring that they are used within their intended scope. Effective model risk management helps organizations avoid significant financial losses and comply with regulatory requirements.
Infographic showing various Model Risk job openings in Louisiana as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, 1% Temporary, and 2% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution.
Cyber AI Data Engineer Senior Consultant

Cyber AI Data Engineer Senior Consultant

Deloitte

New Orleans, LA • On-site

Other

Re-posted 25 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 90 frontline employees who took The Breakroom Quiz

60th of 148 rated financial services


Job description

Are you interested in improving the cyber and organizational risk profiles of leading companies? Do you want to build the data foundations that power the next generation of AI-enabled cyber defense?

If yes, then Deloitte's Cyber team could be the place for you.

We are looking for a hands-on Data Engineer to build and operate the governed data foundations powering cyber risk, compliance evidence, and agentic AI-enabled cyber workflows. You will design production-grade pipelines and services that support risk reporting, continuous controls monitoring, and AI-assisted security operations-built with strong governance, lineage, privacy-by-design, and audit-ready evidence.

This role is ideal for engineers who can bridge modern data engineering and software development with Governance, Risk, and Compliance (GRC) expectations in regulated enterprise environments.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Senior Consultant, Strategy, Growth and Transformation on the Cyber team, you will be responsible for:

  • Building scalable batch and stream processing pipelines that ingest security telemetry, control evidence, and compliance artifacts into governed data stores.
  • Designing data models for risk and controls domains, including key risk indicators, issues and defects, risk acceptance, control testing outcomes, audit evidence, and policy exceptions, and enabling self-service analytics and dashboards.
  • Implementing data quality checks, lineage, metadata, and access controls to support auditability, regulatory defensibility, and repeatable evidence generation.
  • Developing AI-enabled capabilities that accelerate governance, risk, and compliance and cyber operations, including evidence summarization, control testing assist, policy question-and-answer, investigation copilots, ticket triage, and exception reasoning using agentic patterns, workflow orchestration, and retrieval-augmented generation.
  • Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces, event patterns, and connectors, with observability and runbooks for production support.
  • Partnering with Cyber, Risk, Compliance, Privacy, and Legal stakeholders to translate requirements into implementable controls and developer-ready guardrails.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

You will join a cyber engineering team focused on enabling resilient, secure, and compliant operations through modern data platforms and AI-enabled automation. The team builds repeatable assets-reference architectures, accelerators, and governance patterns-to help clients modernize and scale cyber and GRC programs.

Qualifications

Required:

  • Bachelor's degree or equivalent practical experience.
  • 4+ years of experience in data engineering and software development using Python and SQL.
  • Experience building production data pipelines and data models for batch processing, stream processing, or both, and deploying solutions using cloud platforms, containers, infrastructure as code, application programming interfaces, and secrets management.
  • Experience implementing data governance controls including data classification, personally identifiable information handling, least-privilege access, encryption, secrets management, retention, audit logging, and lineage or metadata management.
  • Experience supporting governance, risk, and compliance workflows, including risk reporting, audit data requests, controls monitoring, controls testing, compliance metrics, governance, risk, and compliance tool integrations, and large language model-enabled applications using retrieval-augmented generation, vector or hybrid retrieval, tool or function calling, evaluation or monitoring, prompt-injection defenses, and secure access patterns.
  • Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Experience in consulting or a Big 4 environment.
  • Experience with Java, Go, or JavaScript.
  • Experience integrating with ServiceNow GRC, Archer, OneTrust, or BigID and building evidence pipelines mapped to control objectives.
  • Experience building pipelines for security information and event management, security orchestration, automation, and response, vulnerability, identity, or cloud security posture data.
  • Experience operationalizing large language model operations or machine learning operations capabilities, including evaluation, monitoring, versioning, and governance workflows.
  • Security certification such as CompTIA Security+, Certified Information Security Manager, Certified Information Systems Auditor, Certified Information Systems Security Professional, or a cloud certification.

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 $105,400 to $207,800.

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:

Are you interested in improving the cyber and organizational risk profiles of leading companies? Do you want to build the data foundations that power the next generation of AI-enabled cyber defense?

If yes, then Deloitte's Cyber team could be the place for you.

We are looking for a hands-on Data Engineer to build and operate the governed data foundations powering cyber risk, compliance evidence, and agentic AI-enabled cyber workflows. You will design production-grade pipelines and services that support risk reporting, continuous controls monitoring, and AI-assisted security operations-built with strong governance, lineage, privacy-by-design, and audit-ready evidence.

This role is ideal for engineers who can bridge modern data engineering and software development with Governance, Risk, and Compliance (GRC) expectations in regulated enterprise environments.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Senior Consultant, Strategy, Growth and Transformation on the Cyber team, you will be responsible for:

  • Building scalable batch and stream processing pipelines that ingest security telemetry, control evidence, and compliance artifacts into governed data stores.
  • Designing data models for risk and controls domains, including key risk indicators, issues and defects, risk acceptance, control testing outcomes, audit evidence, and policy exceptions, and enabling self-service analytics and dashboards.
  • Implementing data quality checks, lineage, metadata, and access controls to support auditability, regulatory defensibility, and repeatable evidence generation.
  • Developing AI-enabled capabilities that accelerate governance, risk, and compliance and cyber operations, including evidence summarization, control testing assist, policy question-and-answer, investigation copilots, ticket triage, and exception reasoning using agentic patterns, workflow orchestration, and retrieval-augmented generation.
  • Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces, event patterns, and connectors, with observability and runbooks for production support.
  • Partnering with Cyber, Risk, Compliance, Privacy, and Legal stakeholders to translate requirements into implementable controls and developer-ready guardrails.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

You will join a cyber engineering team focused on enabling resilient, secure, and compliant operations through modern data platforms and AI-enabled automation. The team builds repeatable assets-reference architectures, accelerators, and governance patterns-to help clients modernize and scale cyber and GRC programs.

Qualifications

Required:

  • Bachelor's degree or equivalent practical experience.
  • 4+ years of experience in data engineering and software development using Python and SQL.
  • Experience building production data pipelines and data models for batch processing, stream processing, or both, and deploying solutions using cloud platforms, containers, infrastructure as code, application programming interfaces, and secrets management.
  • Experience implementing data governance controls including data classification, personally identifiable information handling, least-privilege access, encryption, secrets management, retention, audit logging, and lineage or metadata management.
  • Experience supporting governance, risk, and compliance workflows, including risk reporting, audit data requests, controls monitoring, controls testing, compliance metrics, governance, risk, and compliance tool integrations, and large language model-enabled applications using retrieval-augmented generation, vector or hybrid retrieval, tool or function calling, evaluation or monitoring, prompt-injection defenses, and secure access patterns.
  • Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Experience in consulting or a Big 4 environment.
  • Experience with Java, Go, or JavaScript.
  • Experience integrating with ServiceNow GRC, Archer, OneTrust, or BigID and building evidence pipelines mapped to control objectives.
  • Experience building pipelines for security information and event management, security orchestration, automation, and response, vulnerability, identity, or cloud security posture data.
  • Experience operationalizing large language model operations or machine learning operations capabilities, including evaluation, monitoring, versioning, and governance workflows.
  • Security certification such as CompTIA Security+, Certified Information Security Manager, Certified Information Systems Auditor, Certified Information Systems Security Professional, or a cloud certification.

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 $105,400 to $207,800.

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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