Director of Data and Artificial Intelligence

Mutual Bancorp and its Subsidiaries•Hyannis, MA

About The Position

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.

Requirements

Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or related field required; Master's degree or MBA preferred
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
Track record of successfully establishing data or analytics functions from inception
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
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
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.

Nice To Haves

Prior experience in financial services, banking, or highly regulated industries strongly preferred

Responsibilities

Develop and execute a comprehensive data and AI strategy aligned with the bank's business objectives and regulatory environment
Build and champion a data-driven culture across the organization, serving as a thought leader and change agent
Establish governance frameworks, policies, and standards for data management, data quality, and AI ethics
Partner with executive leadership to identify high-value opportunities for data and AI to drive business outcomes
Define and communicate the strategic roadmap for data infrastructure, analytics capabilities, and AI implementation
Design and implement a scalable, secure data architecture that supports analytics, AI/ML, and business intelligence needs
Establish data governance frameworks including data quality standards, metadata management, and data lineage
Implement master data management (MDM) and data integration strategies across disparate banking systems
Develop data lake/lakehouse and data warehouse solutions optimized for both operational and analytical workloads
Create policies and processes for data access, security, privacy, and regulatory compliance (GDPR, CCPA, GLBA, etc.)
Build data cataloging and discovery capabilities to democratize access to trusted data assets
Identify, prioritize, and implement AI and machine learning use cases that deliver measurable business value
Develop responsible AI frameworks addressing ethics, bias mitigation, explainability, and model risk management
Establish MLOps practices for model development, deployment, monitoring, and lifecycle management
Create predictive and prescriptive analytics capabilities for risk management, fraud detection, customer insights, and operational efficiency
Evaluate and implement generative AI solutions while ensuring appropriate controls and risk mitigation
Build experimentation frameworks and proof-of-concept capabilities for emerging technologies
Build, develop, and mentor a high-performing team of data engineers, data analysts, data scientists, and AI specialists
Establish clear roles, responsibilities, and career pathways for data and AI professionals
Foster a culture of innovation, continuous learning, and technical excellence within the team
Develop partnerships with universities, technology vendors, and industry organizations to access talent and insights
Create training programs to upskill staff across the organization on data literacy and AI fundamentals
Partner with business unit leaders to understand needs and translate them into data and AI solutions
Collaborate with IT, cybersecurity, compliance, and risk management to ensure integrated approaches
Manage relationships with technology vendors, consultants, and strategic partners
Present regular updates to executive leadership and board committees on data and AI initiatives
Serve as the primary liaison with regulators on data management and AI-related matters
Select, implement, and manage modern data platforms, tools, and technologies
Ensure data infrastructure scalability, reliability, security, and cost-effectiveness
Establish cloud data strategies and hybrid architecture approaches as appropriate
Implement real-time data processing capabilities and streaming analytics where needed
Oversee API development for data access and integration with internal and external systems