Head of Data, AI and Algorithm Governance
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Key responsibilities:
- Lead a team of data and A.I./algorithm analysts
- Define, maintain, and communicate enterprise data, algorithm and A.I. governance policies
- Collaborate and partner with other leaders including legal, compliance and enterprise risk, and information security to craft and maintain policy
- Establish quantitative measures of policy compliance including data measures such as quality, ethics, veracity, and lineage and algorithm measures that include bias, variance, and performance
- Collaborate with various departments throughout the organization to establish automated processes that collect and compute measures of progress
- Define and maintain a strategic roadmap for governance roll-out
- Create and maintain a meta-data asset that accurately characterizes the firm’s data sources and algorithms through time, as well as their adherence to governance policies
- Identify and engage data stewards across the enterprise for each data domain or business area and coordinate with them to achieve defined program goals
- Work with technology and business functions across the organization to build a shared business glossary and standards around shared data domains to enhance the organization’s ability to leverage data cross-functionally
- Establish working groups to ensure consistency and adoption of governance across data and algorithmic domains
- Develop and implement of algorithm standards and standards of use
- Stay up-to-date and informed on emerging practices for improving data, algorithm and A.I. governance practices
Skills and Qualifications:
Deep financial services knowledge, including core business processes and regulations
- Knowledge of databases, data models, data management, and data quality best practices
- Knowledge of reference data architectures and models for financial services (insurance and retirement plans)
- Knowledge of methods in machine learning and artificial intelligence
- Knowledge of metrics associated with characterizing performance, bias, variance, and error of algorithms and predictive models
- Experience in building enterprise programs around data management, algorithm management
- Experience creating KPIs and using them to manage execution and inform strategy
- Exceptional communication skills, both written and verbal
- Exceptional influencing abilities across all levels of the organization
- Extensive experience establishing and executing complex, strategic, cross-functional enterprise programs
- Deep financial services knowledge, including core business processes and regulations
- Advanced degree (M.S. or Ph.d) in STEM or relevant field preferred.
- Must be authorized to work in the US without sponsorship now and in the future.
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