Director of Data and Artificial Intelligence

SUMMARY:

We are seeking a visionary and strategic Director of Data and AI to establish and lead our organization's dedicated data and artificial intelligence function. This is a transformational leadership opportunity to continue to build our data and AI capabilities, driving innovation and competitive advantage across our banking operations. Reporting directly to the Chief Information Officer, this role will be responsible for developing our data ecosystem, implementing AI solutions and establishing the organizational capabilities needed to become a data-driven financial institution.

ESSENTIAL JOB FUNCTIONS/RESPONSIBILITIES:

Strategic Leadership & Vision

1. Develop and execute a comprehensive data and AI strategy aligned with the bank's business objectives and regulatory environment
2. Build and champion a data-driven culture across the organization, serving as a thought leader and change agent
3. Establish governance frameworks, policies, and standards for data management, data quality, and AI ethics
4. Partner with executive leadership to identify high-value opportunities for data and AI to drive business outcomes
5. Define and communicate the strategic roadmap for data infrastructure, analytics capabilities, and AI implementation

Data Ecosystem Development

1. Design and implement a scalable, secure data architecture that supports analytics, AI/ML, and business intelligence needs
2. Establish data governance frameworks including data quality standards, metadata management, and data lineage
3. Implement master data management (MDM) and data integration strategies across disparate banking systems
4. Develop data lake/lakehouse and data warehouse solutions optimized for both operational and analytical workloads
5. Create policies and processes for data access, security, privacy, and regulatory compliance (GDPR, CCPA, GLBA, etc.)
6. Build data cataloging and discovery capabilities to democratize access to trusted data assets

AI & Advanced Analytics

1. Identify, prioritize, and implement AI and machine learning use cases that deliver measurable business value
2. Develop responsible AI frameworks addressing ethics, bias mitigation, explainability, and model risk management
3. Establish MLOps practices for model development, deployment, monitoring, and lifecycle management
4. Create predictive and prescriptive analytics capabilities for risk management, fraud detection, customer insights, and operational efficiency
5. Evaluate and implement generative AI solutions while ensuring appropriate controls and risk mitigation
6. Build experimentation frameworks and proof-of-concept capabilities for emerging technologies

Team Building & Leadership

1. Build, develop, and mentor a high-performing team of data engineers, data analysts, data scientists, and AI specialists
2. Establish clear roles, responsibilities, and career pathways for data and AI professionals
3. Foster a culture of innovation, continuous learning, and technical excellence within the team
4. Develop partnerships with universities, technology vendors, and industry organizations to access talent and insights
5. Create training programs to upskill staff across the organization on data literacy and AI fundamentals

Stakeholder Management & Collaboration

1. Partner with business unit leaders to understand needs and translate them into data and AI solutions
2. Collaborate with IT, cybersecurity, compliance, and risk management to ensure integrated approaches
3. Manage relationships with technology vendors, consultants, and strategic partners
4. Present regular updates to executive leadership and board committees on data and AI initiatives
5. Serve as the primary liaison with regulators on data management and AI-related matters

Technology & Infrastructure

1. Select, implement, and manage modern data platforms, tools, and technologies
2. Ensure data infrastructure scalability, reliability, security, and cost-effectiveness
3. Establish cloud data strategies and hybrid architecture approaches as appropriate
4. Implement real-time data processing capabilities and streaming analytics where needed
5. Oversee API development for data access and integration with internal and external systems

QUALIFICATIONS:

EDUCATION, CERTIFICATIONS:

• Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or related field required; Master's degree or MBA preferred

KNOWLEDGE, SKILLS & ABILITIES:

• 10+ years of progressive experience in data management, analytics, or AI/ML roles required
• 5+ years in leadership positions with demonstrated team-building experience required
• Prior experience in financial services, banking, or highly regulated industries strongly preferred
• Track record of successfully establishing data or analytics functions from inception

Technical Expertise

• Deep understanding of modern data architecture patterns (data lakes, lakehouses, data mesh, etc.)
• Strong knowledge of data governance, data quality management, and master data management
• Expertise in AI/ML technologies, including supervised/unsupervised learning, NLP, and generative AI
• Proficiency with cloud platforms (AWS, Azure, GCP) and their data/AI services
• Familiarity with data engineering tools, ETL/ELT processes, and DataOps/MLOps practices
• Understanding of data visualization, business intelligence, and analytics tools

Business & Leadership Skills

• Strategic thinking with ability to translate business needs into technical solutions
• Exceptional communication skills with ability to explain complex concepts to non-technical stakeholders
• Proven change management capabilities in driving organizational transformation
• Strong project management skills with experience managing multiple initiatives simultaneously
• Financial acumen including budget management, ROI analysis, and business case development

Industry Knowledge

• Understanding of banking operations, products, and customer lifecycle
• Knowledge of financial services regulations (BSA/AML, KYC, GDPR, Fair Lending, etc.)
• Familiarity with model risk management and regulatory expectations for AI in banking
• Awareness of industry trends in fintech, open banking, and digital transformation
• Must have cyber security awareness to protect the digital environment, the Bank, and customers.