What are the responsibilities and job description for the Data and Responsible AI Governance Lead position at Nasscomm?
Role: Data and Responsible AI Governance Lead
Location: St. Louis, MO
Duration: 6-12 Months
Job Summary
We are seeking a Data and Responsible AI Governance Lead to define, operationalize, and continuously improve the governance framework for data and AI across the enterprise. This role will lead policies, controls, and oversight mechanisms that promote ethical, compliant, secure, and business-aligned use of data and AI solutions. The ideal candidate brings deep experience in data governance, AI risk management, regulatory compliance, and cross-functional stakeholder leadership.
Key Responsibilities
•Lead the design and implementation of enterprise-wide data and Responsible AI governance frameworks, standards, and operating models.
•Establish policies and controls for data quality, data lineage, access management, model transparency, fairness, explainability, privacy, and monitoring.
•Oversee governance processes for AI use cases, including intake, risk assessment, approval, exception management, and ongoing review.
•Partner with legal, compliance, cyber, technology, risk, and business teams to ensure governance practices align with internal policies and external regulatory requirements.
•Define roles, decision rights, and accountability across data owners, model owners, developers, risk, and control functions.
•Develop and track KPIs, KRIs, and governance reporting for executive leadership and governance committees.
•Support model and AI lifecycle governance, including documentation, testing, validation, deployment controls, and post-production monitoring.
•Drive awareness and adoption of Responsible AI principles through training, communications, and change management.
•Monitor emerging regulations, industry standards, and leading practices related to data governance and AI governance, and translate them into practical enterprise actions.
•Identify governance gaps and lead remediation plans to strengthen control effectiveness and business adoption.
Required Qualifications
•Bachelor’s degree in Data, Computer Science, Information Systems, Risk, Law, Public Policy, or a related field.
•8 years of experience in data governance, AI governance, risk management, compliance, or a related field.
•Experience building or leading governance programs for data, analytics, machine learning, or generative AI.
•Strong understanding of Responsible AI principles, including fairness, accountability, transparency, privacy, safety, and human oversight.
•Knowledge of relevant regulatory and risk domains such as data privacy, model risk, information security, and records management.
•Demonstrated ability to influence senior stakeholders and lead cross-functional initiatives in complex organizations.
•Strong written and verbal communication skills, with the ability to translate technical and regulatory topics into business decisions.
Success Profile
•Strategic thinker with strong execution discipline.
•Comfortable balancing innovation, control, and business enablement.
•Strong judgment, credibility, and stakeholder management skills.
•Able to operate effectively in ambiguity and build structure where it does not yet exist.
Sample Outcomes for the First 12 Months
•Stand up a formal Responsible AI governance process and committee structure.
•Launch enterprise standards for high-risk AI use cases and model documentation.
•Implement governance reporting for leadership on data and AI risk posture.
•Improve compliance, transparency, and decision traceability across priority AI initiatives.