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Director Model Risk Governance Jobs in Connecticut

Northwest Community Bank

RISK ANALYST

Canton, CT · On-site

... model risk. * Track, manage, monitor, and report on risk issues and corrective action plans to ... Familiarity with Governance, Risk, and Compliance (GRC) systems preferred * Professional ...

Northwest Community Bank

RISK ANALYST

Canton, CT · On-site

... model risk. * Track, manage, monitor, and report on risk issues and corrective action plans to ... Familiarity with Governance, Risk, and Compliance (GRC) systems preferred * Professional ...

Factset

Director, Technology Risk

Norwalk, CT · On-site

Define a technology risk taxonomy and scoring model** that incorporates risk severity, business ... Establish governance forums and reporting cadences that deliver timely, actionable risk insights to ...

Munich RE

Enterprise Risk Lead

Hartford, CT · On-site +1

Risk Governance & Reporting Lead (Project Management) We are adding to our diverse team of experts ... Proven ability to influence outcomes in a matrixed organization without direct authority. * Project ...

Munich Re

Enterprise Risk Lead

Hartford, CT · On-site +1

Risk Governance & Reporting Lead (Project Management) We are adding to our diverse team of experts ... Proven ability to influence outcomes in a matrixed organization without direct authority. * Project ...

TecTammina

OFSAA data modeler

Norwalk, CT

$55 - $71.25/hr

... Data governance, data quality, Data Profiling & Data analysis related to Regulatory Reporting OFSAA Implementation experience for regulatory reporting like Model risk management, Liquidity Risk ...

TecTammina

OFSAA data modeler

Norwalk, CT

$55 - $71.25/hr

... Data governance, data quality, Data Profiling & Data analysis related to Regulatory Reporting OFSAA Implementation experience for regulatory reporting like Model risk management, Liquidity Risk ...

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Director Model Risk Governance information

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

To thrive as a Director of Model Risk Governance, you need deep expertise in quantitative finance, risk management, and model validation, often backed by an advanced degree in a quantitative field and relevant industry experience. Familiarity with risk management frameworks, regulatory standards (e.g., SR 11-7), and proficiency in analytical tools like Python, R, or SAS are typically required. Exceptional leadership, communication, and critical thinking skills help you effectively oversee teams and coordinate with stakeholders across the organization. These competencies are vital to ensure robust model governance, regulatory compliance, and informed risk-based decision-making at the enterprise level.

What are some common challenges faced by a Director of Model Risk Governance, and how can they be addressed?

A Director of Model Risk Governance often encounters challenges such as ensuring consistent model validation across diverse business units, keeping up with evolving regulatory requirements, and fostering effective communication between model owners, validators, and senior management. Addressing these challenges typically involves establishing robust model risk frameworks, maintaining clear documentation, and promoting a culture of transparency and collaboration. Regular training sessions and open forums can help bridge knowledge gaps, while leveraging technology can streamline model inventory and validation processes.

What are Director Model Risk Governance roles?

Director Model Risk Governance roles are senior positions responsible for overseeing and managing the risks associated with financial and predictive models within an organization. These professionals establish and implement model risk management frameworks, ensure compliance with regulatory requirements, and oversee model validation processes. They collaborate with model developers, validators, and business units to identify, assess, and mitigate model risks, as well as report on governance effectiveness to senior management. Their work is crucial in maintaining the reliability and integrity of models used for decision-making and regulatory reporting.

What is the difference between Director Model Risk Governance vs Model Risk Analyst?

AspectDirector Model Risk GovernanceModel Risk Analyst
CredentialsAdvanced degrees (e.g., Master’s, PhD), professional certifications (e.g., FRM, CFA)Bachelor’s or Master’s degree, relevant certifications
Work EnvironmentStrategic oversight, policy development, senior stakeholder engagementData analysis, model validation, risk assessment
Employer & Industry UsageFinancial institutions, banks, asset managersFinancial institutions, risk management teams
Search & Comparison IntentUnderstanding leadership roles in model risk governanceEntry to mid-level model risk roles, analysis tasks

The main difference is that the Director Model Risk Governance focuses on strategic oversight, policy setting, and managing model risk at a senior level, while the Model Risk Analyst handles technical validation, data analysis, and risk assessment tasks. The director role involves leadership and decision-making, whereas the analyst role is more technical and operational.

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What job categories do people searching Director Model Risk Governance jobs in Connecticut look for? The top searched job categories for Director Model Risk Governance jobs in Connecticut are:
What cities in Connecticut are hiring for Director Model Risk Governance jobs? Cities in Connecticut with the most Director Model Risk Governance job openings:
Director Model Risk Governance jobs near you
Director Model Risk Management - AI/Gen AI

Director Model Risk Management - AI/Gen AI

The Hartford Financial Services Group, Inc.

Hartford, CT • On-site

Full-time

Posted 6 days ago

The Hartford rating

8.8

Company rating: 8.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz

53rd of 259 rated insurance

Job description

Director Model Risk Management - KM06AE
We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.
Director Model Risk Management AI/GenAI
The Hartford's Model Risk Management function seeks a director to join a talented and high-performing Model Risk Management team. The successful candidate will lead efforts to ensure the integrity, accuracy, and compliance of AI and Generative AI (GenAI) models used across the enterprise. The Director/Validator will independently review, challenge, and validate models to ensure they meet internal model risk management standards, regulatory expectations, and ethical AI principles. In addition, the Director will drive the enhancement of the existing model validation framework for GenAI including identifying and deploying model validation tools for increased efficiency.
The Hartford utilizes advanced analytics, predictive, AI/ML, and Generative AI models as well as traditional actuarial models in a variety of important and critical business functions. The Model Risk Management team manages model risk across The Hartford by validating these models, implementing consistent policies and standards, and maintaining appropriate model oversight. As part of the team, this role will focus primarily on validating AI and GenAI models across The Hartford and reporting results to key internal stakeholders. Additional responsibilities include educating modeling best practices and spreading model risk awareness across the enterprise.
Responsibilities
  • Model Validation and Oversight: Direct and perform end-to-end model validations on AI and GenAI model use cases across The Hartford's functional areas and lines of business:
    • Ensure model calculations, machine learning algorithms, and GenAI methods are accurate and appropriate for intended use.
    • Design and build challenger solutions and testing methods for tasks such as summarization, question answering, search, data synthesis, LLM-as-a-judge, Context Relevancy, Answer Relevancy, Groundedness etc.
    • Review and assess the quantitative and qualitative testing techniques to ensure model accuracy, robustness, and reliability.
    • Assess key data inputs, assumptions, prompt engineering, context engineering for accuracy and appropriateness.
    • Review model outputs for accuracy and appropriate downstream usage.
    • Deliver effective challenge to key modeling elements such as inputs, calculations, outputs, conceptual soundness, monitoring & controls, documentation, etc.
    • Assess the appropriate use of model / use case controls, e.g., Guardrails, HITL/HOTL, their implementation and effectiveness across a variety of models and use cases.
  • Identify findings and recommendations, including impact analysis, to mitigate model risk and compile clear and concise model validation reports.
  • Perform governance accountabilities related to findings tracking, remediation testing, and validation.
  • Governance, Framework, and Practice Enhancement: Drive end-to-end initiatives including the enhancement of the existing GenAI model validation framework:
    • Assist in the continuous improvement of The Hartford's Model Risk Management function by monitoring external environment, recommending process improvements, implementing emerging best practices, and evolving the enterprise's model risk management Policy and Standards for Model Development and Use
    • Identifying and deploying model validation tools for increased efficiency, while ensuring the continued alignment with regulatory standards
    • Identify/develop qualitative assessments and quantitative performance metrics to test and monitor AI/ML and GenAI performance and reliability, including model drift detection, data currency, lineage, quality, integrity, and inform model validation practices (e.g., scope, frequency)
    • Pro-actively stay informed of advancements in AI/ML, GenAI modeling and associated emerging techniques/technologies, their application, risks, and risk mitigating strategies.
    • Lead initiatives to understand and upskill for tools, such as VertexAI/Google agent development kit, LangChain/LangGraph, RAG frameworks, HuggingFace, OpenAI APIs, etc.
  • Strategic Collaboration: Strengthen enterprise partnerships with leadership and their teams across Data Science, Tech, PIDA, Actuarial and the Lines of Business to:
    • Deliver insights that enhance model development, performance, and reliability, ensuring a comprehensive approach to risk management and business strategy.
    • Keep model risk practices aligned with the proliferation and sophistication of modeling by partnering on cross functional teams (e.g., Audit Readiness) to advance Standard Work Templates and best practices for proactive model risk management.
    • Pro-actively stay informed of enterprise and Line of Business initiatives, deliverables, and reporting.

Qualifications
  • Advanced degree (M.S. or Ph.D.) in a relevant field e.g., Artificial Intelligence, Machine Learning, Computational Science, Engineering, Statistics, Applied Mathematics, Actuarial Science, Quantitative Economics.
  • 10+ years of industry experience in machine learning or data science and with 1+ years focused on GenAI.
  • Strong understanding of enterprise-wide governance and risk management frameworks.
  • P&C, Group, Life, or related insurance product experience is a plus.
  • Strong programming experience across languages/technology platforms including Python, R, SAS/SQL
  • Solid understanding of GenAI concepts including prompt and context engineering, retrieval-augmented generation (RAG), agent workflow, LLM evaluation, familiarity with neural networks
  • Experience in GenAI tools such as Vertex AI/Google agent development kit, LangChain/LangGraph, RAG frameworks, HuggingFace, OpenAI APIs.
  • Ability to act independently with proactive self-directed accountability and demonstrated experience and consistency in meeting deadlines while adapting to shifting priorities.
  • Strong analytical, critical, and investigative thinking skills
  • Demonstrated commitment to lifelong learning with an ardent desire for continuous development to keep pace with evolving modeling techniques and AI technologies.
  • Solution oriented creativity, innovative thinking, and challenging the status quo.
  • Excellent communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders across the enterprise.

Compensation
The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford's total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:
$136,000 - $204,000
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
About Us | Our Culture | What It's Like to Work Here | Perks & Benefits

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About Hartford

Sourced by ZipRecruiter

Hartford Financial Services Group, widely recognized as The Hartford, is a renowned company based in Hartford, CT, US. Established in 1810, it has evolved into an industry leader in the insurance and financial services sector, proudly serving more than one million businesses in the US. The Hartford is committed to offering a gamut of insurance products that include homeowners, automobile, and business insurance as well as employee benefits and mutual funds. The company’s core values revolve around customer-focused innovations, diversity and inclusion, and ethical dealings that have earned them a customer-centric reputation. This shapes their mission which revolves around aiding their clients to overcome unforeseen obstacles and enhancing their wealth over time. Among the company's noted accomplishments is being consistently listed among the World's Most Ethical Companies, a testament to their unwavering commitment towards responsible business practices.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

Hartford, CT, US

Year founded

1810

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