1

Director Model Risk Governance Jobs in Indiana (NOW HIRING)

Enterprise Architect (IT)

Indianapolis, IN · On-site +1

$66 - $85/hr

  • Medical

  • Life

  • Retirement

  • PTO

Reporting to the Director of Enterprise Architecture, this role partners with business, technology ... Familiarity with AI governance, model risk considerations, responsible AI principles, data ...

Enterprise Architect (IT)

Indianapolis, IN · On-site +1

$102K - $208K/yr

  • Medical

  • Life

  • Retirement

  • PTO

Reporting to the Director of Enterprise Architecture, this role partners with business, technology ... Familiarity with AI governance, model risk considerations, responsible AI principles, data ...

Showing results 21-40

Director Model Risk Governance information

What is a director model risk governance?

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 are the key skills and qualifications needed to thrive as a director model risk governance?

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 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 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.

What are the most commonly searched types of Model Risk Governance jobs in Indiana?

The most popular types of Model Risk Governance jobs in Indiana are:

What are popular job titles related to Director Model Risk Governance jobs in Indiana?

For Director Model Risk Governance jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Director Model Risk Governance jobs in Indiana look for?

The top searched job categories for Director Model Risk Governance jobs in Indiana are:

What cities in Indiana are hiring for Director Model Risk Governance jobs?

Cities in Indiana with the most Director Model Risk Governance job openings:

Infographic showing various Director Model Risk Governance job openings in Indiana as of August 2026, with employment types broken down into 100% Full Time. Highlights an 46% In-person, and 54% Remote job distribution.

Senior Director, Data Governance and Stewardship

Cook Group

Bloomington, IN • On-site

$120 - $160/hr

Other

Re-posted yesterday


Job description

Overview

The Senior Director, Data Governance and Stewardship leads the enterprise-wide evolution of how Cook Medical understands, owns and acts on its data. This role provides strategic leadership for data governance across Cook's enterprise platforms — spanning traditional systems including ERP, CRM, and reporting environments — as well as Palantir Foundry, Cook's ontology-driven intelligence and agentic AI layer. The role partners with business leaders to ensure data is consistently defined, business-owned and governed to a common standard across all platforms, while partnering closely with IT and AI on technical implementation to ensure the proper infrastructure is in place.

Responsibilities

Data Governance Strategy & Operating Model

  • Evolve and advance Cook Medical’s enterprise data governance framework, operating model, and policy standards to keep pace with the organization’s growing data and AI ambitions.
  • Strengthen the Data Governance Councils with cross-functional executive representation; serve as chair or co-chair alongside a senior business sponsor.
  • Maintain and advance a data governance roadmap that prioritizes domains based on business impact, maximizing business value, managing regulatory exposure, reducing risk, and enabling AI/agentic use case readiness.
  • Define and refine governance policies, standards, and processes covering data ownership, stewardship, quality, classification, definitions, and lifecycle management.

Business Data Ownership & Stewardship

  • Formalize and expand Data Owner assignments across Cook’s critical data domains (e.g., Customer, Product, Supplier, Financial, Regulatory/Clinical, Employee).
  • Enable and grow the network of Business Data Stewards embedded within functional areas; refine roles, accountabilities, and operating rhythms to improve engagement and effectiveness.
  • Maintain and expand the Business Glossary and enterprise data dictionary, ensuring shared, unambiguous definitions across business units, systems, and geographies.
  • Ensure data ownership is embedded in business processes — not just org charts — with owners actively participating in quality remediation, definition management, and governance decisions.

Data Literacy & Change Management

  • Partner with HR, Learning and Talent Development to support a multi-year literacy program building foundational Data/AI fluency across Cook’s business functions, from frontline users to senior leadership.
  • Champion the organizational shift from “IT/AI owns data” to “the business owns data, IT/AI enables it.”
  • Measure and report governance adoption metrics; identify where additional investment, enablement, or escalation is needed.
  • Serve as an internal advocate — positioning data governance as a business enabler, not a compliance burden.

Master Data Management (Business Process Ownership)

  • Partner with IT, data engineering and AI to advance Cook’s MDM program, providing business-side requirements, ownership assignments, and quality standards for master data entities.
  • Lead the definition of MDM domains and canonical entities, establishing golden record standards for customer, product, supplier, and related data objects while aligning business stakeholders to governance definitions.
  • Oversee the business processes that create, maintain, and retire master data; identify workflow gaps that introduce quality issues and drive process improvement.
  • Ensure MDM standards are applied consistently across both traditional enterprise platforms and Palantir Foundry.

Cross-Platform Data Governance

  • Establish and enforce consistent governance standards spanning Cook’s traditional enterprise platforms and Palantir Foundry — ensuring data definitions, quality standards, ownership assignments, and access policies are coherent across environments.
  • Serve as the business-side governance authority for Cook’s Palantir Foundry ontology, ensuring objects, properties, and relationships reflect business-owned definitions through a formal review and approval process.
  • Partner with IT/AI architecture, data engineering, and the Palantir program team to ensure governance is designed into platform decisions, not retrofitted after the fact.
  • Maintain cross-platform data lineage, enabling stakeholders to trace data from source systems through to Palantir Foundry with clear business ownership at each stage.

Cross-Functional Leadership & Stakeholder Engagement

  • Build and maintain trusted relationships with senior leaders across Finance, Commercial, Operations, Supply Chain, R&D, Regulatory, Legal and HR — positioning data governance as a shared business priority.
  • Partner with Compliance and Legal to ensure governance policies address applicable regulatory obligations (e.g., MDR, FDA, GDPR, HIPAA) etc.
  • Report on governance program health, maturity, and business impact to executive leadership; contribute to the annual data strategy narrative.

Team & Program Leadership

  • Lead and develop a high-impact governance team; define team structure and cultivate team members’ capabilities.
  • Provide business requirements when selecting and implementing governance tooling (e.g., data catalog, business glossary, data quality monitoring) in partnership with IT and AI.
  • Manage governance program budget and vendor relationships.
Qualifications
  • Bachelor's degree in Business, Information Systems, Data Management, or a related field; advanced degree preferred.
  • 12+ years of progressive experience in data management, data governance, or a related business function; at least 5 years in a senior leadership role.
  • Certification in data management (CDMP, DCAM) or change management (Prosci, Kotter) highly regarded.
  • Demonstrated success advancing enterprise data governance programs, including operating models, policy frameworks, and stewardship structures.
  • Deep understanding of data governance frameworks (DAMA‑DMBOK or equivalent) and how to apply them pragmatically in a complex, global organization.
  • Track record of driving adoption in organizations where data literacy was low and IT historically owned data - comfortable working in a fast-paced agile environment with evidence of measurable cultural change.
  • Strong executive presence and communication skills; able to translate data concepts fluently for non-technical business audiences and influence without direct authority.
  • Proven people-leadership skills; able to translate data concepts fluently for non-technical business audiences and influence without direct authority.
  • Master Data Management (MDM) program leadership experience: defining golden record requirements and managing master data quality with business stakeholders.
  • Experience establishing data quality metrics, monitoring, and remediation processes, and report on data quality and governance health to executive leadership.
  • Experience partnering with IT, data engineering, AI and analytics teams on MDM, data architecture, and data quality programs.
  • Ability to establish consistent governance standards across multiple platforms or data layers, ensuring coherence between integration and intelligence environments.
  • Experience with Microsoft Data platforms, Oracle Data platforms and Palantir Foundry, including familiarity with ontology concepts, data catalog capabilities, and governance roles across the platforms.
  • This role requires mastery in Artificial Intelligence (AI) and data concepts, including the ability to assess feasibility and risk of AI use cases, design or coordinate workflow-level AI solutions, guide teams on responsible AI governance, mentor others, and contribute to organizational policies and ethical decision-making.
  • Familiarity with AI/Machine Learning (ML) governance considerations and how data governance intersects with the reliability and trustworthiness of agentic AI workflows.
  • Experience governing data through a major enterprise application transformation (ERP, CRM, or equivalent), including embedding data standards and ownership before go‑live.
  • Background in regulated industries — medical devices, life sciences, pharmaceuticals, or manufacturing — where data integrity carries regulatory consequences.
  • Sound knowledge of data privacy, security, and regulatory considerations relevant to a global medical device company (e.g., MDR, FDA, GDPR, HIPAA).
  • Experience in global, multi-entity environments with geographically distributed business units.
  • Experience with data mesh or federated governance models in complex organizations.
Physical Requirements
  • Requires normal range of hearing and eyesight to record, prepare and communicate appropriate reports.
  • Requires lifting papers or boxes up to 25 pounds occasionally. Work is performed in an office environment.
  • Occasional travel may be required (up to 50%).
  • Requires prolonged sitting, some bending, stooping and stretching.
  • Requires eye‑hand coordination and manual dexterity sufficient to operate a keyboard, photocopier, telephone, calculator and other office equipment.
  • Contact may involve dealing with angry or upset people.
#J-18808-Ljbffr