AI & Data Director - Data Lifecycle Management
Listed on 2026-08-24
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IT/Tech
AI Engineer (Applied/Software), IT Project Manager, Data Engineering
Director Of Data Management
This Director manages and directs the execution of data management strategies, overseeing the development and deployment of data management solutions, both business and technical, to enhance business processes and system performance. Leads cross-team collaboration, drives innovation and continuous improvement, enforces governance standards, manages multiple teams, and influences leadership business decisions by designing and implementing solutions to solve real-world challenges.
Essential duties and responsibilities following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time.
Qualifications required qualifications the requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
- Bachelor's degree in Computer Science, Data Science, AI, Software Engineering, or related field.
- Minimum of 10 years of professional experience in AI and data with progressive management responsibilities.
- Proven experience managing teams and delivering AI and data-driven solutions.
- Strong knowledge of AI models, data architectures, and analytics methodologies.
Preferred qualifications
- Master's degree in a relevant technical or business discipline.
- Experience in the financial services industry.
- Expertise in solution designs based upon business requirements.
- Strong knowledge of unstructured data management, retention, and disposition tools and technologies.
- Experience in building financial services strategies for managing the lifecycle of unstructured data for use with AI.
- Familiarity with regulatory compliance and data governance frameworks
- Experience designing and implementing business and technical controls to mitigate data and AI risks within business processes.
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