Director - Data, Privacy and AI Governance
$67K-$135K (Glassdoor est.)
What great looks like in this role


Data, analytics, and artificial intelligence models are at the core of MassMutuals digital transformation. The enterprise Data, Privacy and AI governance program is responsible for implementing a principles-driven, enterprise program that holistically addresses governance at scale and enables the delivery of superior customer value, experiences, trust and loyalty.

As a member of the new Data, Privacy and AI governance team you will work with data scientists and other leaders across the organization on principles, policies, and controls that inventory, measure, assess, and organize the firms data assets and algorithmic models. You will focus on driving change by democratizing data, analytics and AI/ML across the enterprise consistent with our corporate values, customer expectations, and regulations. Our tactics include an initiative to develop a proprietary, self-service platform for unified expression of these governance policies, streaming governance evidence, and a single-pane-of-glass to observe adherence. On our flat, agile team your focus may shift between data governance, privacy governance, and AI governance outcomes over time.

Objectives of the role
Partner with data scientists and business leaders and lead the execution of governance engagements from start to finish. This includes the engagement planning, directing, and completing data and model inventories, compliance and privacy assessments, adoption of our principles-driven, adaptive policy framework, and overall data, privacy and AI/ML governance program objectives.
Contribute to the development of our principles-driven, adaptive policy framework to inventory, assess, organize, measure, and track MassMutuals data and AI/ML assets across the enterprise.
Ensure successful adoption and continuous improvement of the framework to drive effective governance at scale across our data, analytics, privacy and AI/ML capabilities.
Stay up-to-date on emerging trends in consumer expectations, our competitive landscape, and the regulatory environment.
Daily and Monthly Responsibilities
Collaborate and partner with leaders across our data science team, business channels, law, compliance, enterprise risk, and information security for policy making and best practices.
Develop and implement data and AI/ML principles, standards and standards of use.
Establish and track quantitative measures of policy compliance including veracity, lineage, ethics, security, fairness, accountability, transparency, and auditability.
Establish and continuously improve processes that collect governance evidence and compute these measures.
Partner with Enterprise Architecture and Data Management counterparts to drive a cohesive, consistent stakeholder experience and permissible use of data and AI/ML assets based.
Support strategic planning for data, privacy and AI/ML governance and overall data strategy through roadmap development and objective planning
Basic Qualifications
Bachelors degree in Science, Technology, Engineering or Mathematics (STEM).
Experience executing enterprise governance programs in highly regulated industries.
Experience conducting privacy or security risk assessments, DSARs, or internal audits.
Experience creating KPIs and using them to manage execution and inform strategy.
Exceptional communication skills, both written and verbal.
Influencing abilities across all levels of the organization.
Experience working with global privacy and data protection regulations such as the GDPR, CCPA, HIPAA, GLBA and other relevant privacy regulations.
Knowledge of metrics associated with characterizing performance, bias, variance, and error in algorithms and predictive models.
Experience establishing and executing complex, strategic, cross-functional enterprise programs.
Authorized to work in the USA without sponsorship.
Preferred Qualifications
Advanced degree preferred (M.S., M.B.A., J.D.).
Knowledge of public policy making
Experience with technology product management
Knowledge of methods for designing, developing, testing, peer-reviewing, and deploying machine learning and artificial intelligence solutions.
Expertise with the following are considered a strong plus: software development/DevOps, agile methodologies, financial/insurance industry structure and practices, and financial industry regulations.
Work in Boston Office.
Some travel to Springfield, Amherst and New York.
MassMutual
3.6
MassMutual
