Senior Data Governance Professional

At Cotality, we are driven by a single mission-to make the property industry faster, smarter, and more people-centric. Cotality is the trusted source for property intelligence, with unmatched precision, depth, breadth, and insights across the entire ecosystem. Our talented team of 5,000 employees globally uses our network, scale, connectivity and technology to drive the largest asset class in the world. Join us as we work toward our vision of fueling a thriving global property ecosystem and a more resilient society.

Cotality is committed to cultivating a diverse and inclusive work culture that inspires innovation and bold thinking; it's a place where you can collaborate, feel valued, develop skills and directly impact the real estate economy. We know our people are our greatest asset. At Cotality, you can be yourself, lift people up and make an impact. By putting clients first and continuously innovating, we're working together to set the pace for unlocking new possibilities that better serve the property industry.

Job Description:

The Enterprise Data & Model Governance Program team has the mission to establish data and artificial intelligence as strategic assets, delivering continuous business value while ensuring the responsible, secure, and compliant use of data and models. The team engages closely with business stakeholders, data scientists, machine learning (ML) engineers, technology teams, data architects, operations, and legal/compliance to build, scale, and implement comprehensive Data, Model, and AI governance capabilities.

The Senior Data Governance Professional independently plans, completes assignments, sets goals, and collaborates with stakeholders. This role combines technical expertise with strategic thinking to establish and maintain data governance frameworks that support business objectives, ensuring data quality, integrity, and compliance across the organization.

Key Responsibilities:

• Develop operating models and processes to build foundational capabilities, including enterprise data and AI catalogs, model registries, feature stores, data/model access management, and the creation of unified policies and standards.
  
• Establish and enforce comprehensive policies and standards for effective management throughout the entire Data and AI lifecycles (from data ingestion and model training to deployment, monitoring, and retirement).
  
• Design and implement frameworks for Model and AI Governance to ensure algorithmic fairness, transparency, explainability, and the active monitoring/mitigation of model drift and bias.
  
• Act as a critical liaison with Compliance, Legal, and Information Security teams to manage data and AI risks, ensuring adherence to global data privacy laws (e.g., GDPR, CCPA) and emerging AI regulations/frameworks (e.g., EU AI Act, NIST AI RMF).
  
• Roll out and integrate governance processes with enterprise workflows, including MLOps, DataOps, PMO, and agile software development life cycles.
  
• Establish robust change management processes to ensure foundational data dictionaries, AI inventories, and model components are kept up to date.
  
• Support Data and AI Stewards across various business units in the practical implementation and scaling of governance capabilities.
  
• Continuously incorporate emerging best practices and developments from the modern data management, machine learning, and AI industries to drive innovation and business value generation.
  

Job Qualifications:

• 7-10 years of experience in any of the following disciplines: Data Management/Governance, AI/Model Governance, Regulatory Compliance, Risk Management, or Data Science/Analytics.
  
• Bachelor's degree or equivalent experience in a business, technology, or quantitative field (e.g., Computer Science, Data Science, Information Systems).
  
• Solid understanding of the Software Development Life Cycle (SDLC), Data Life Cycle (DLC), and Machine Learning Operations (MLOps) lifecycle.
  
• Familiarity with modern data architectures (e.g., cloud data warehouses, data lakes, unstructured data, vector databases) and the lifecycle of predictive and generative AI models.
  
• Knowledge of AI risk management frameworks (e.g., NIST AI RMF) and practical approaches to Responsible/Ethical AI.
  
• Strong interpersonal and collaborative skills, with a proven ability to work in a matrixed environment, successfully bridging technical (engineering/data science) and non-technical (legal/business) teams.
  
• Strong verbal and written communication skills, capable of translating complex AI/Data concepts to executive stakeholders.
  
• Strong analytical skills, the ability to thrive in ambiguity, and a genuine excitement