Director of Data Analytics & AI

Job Description

Job Title:

Director of Data Analytics and AI

Job Summary: Oversee enterprise data analytics, data governance, business intelligence, and artificial intelligence strategy and operations for the Bank. Lead the development and delivery of secure, compliant, and scalable analytics and AI capabilities that support strategic decision-making, operational efficiency, risk management, and customer experience. Establish and maintain data management, model governance, and AI risk management practices aligned with regulatory expectations and industry standards. Collaborate with business units to implement data-driven solutions while ensuring strong controls over data quality, privacy, model risk, and third-party technology providers.

The scope of responsibility includes enterprise data architecture, data warehousing and reporting platforms, BI tools, advanced analytics, AI/ML solutions, model lifecycle governance, data quality controls, and analytics-related vendor platforms across cloud and on-premises environments.

Essential Functions

The following is a list of essential functions, which may be subject to change at any time and without advance notice. Management may assign new duties, reassign existing duties, or eliminate a function.

• Develop and implement the Bank’s enterprise data analytics and AI strategy aligned with business goals, risk appetite, and regulatory expectations.
• Collaborate with the CIO and executive leadership on strategic planning, innovation initiatives, and risk assessments related to data and AI capabilities.
• Establish and lead a formal data governance framework including data ownership, stewardship, classification, quality standards, lineage, and retention controls.
• Oversee enterprise reporting, dashboards, and analytics platforms to support finance, risk, operations, compliance, lending, and customer analytics.
• Lead development and controlled adoption of AI and advanced analytics use cases, ensuring appropriate validation, transparency, monitoring, and human oversight.
• Implement and maintain model and AI lifecycle controls including development standards, testing, validation support, performance monitoring, change control, and documentation.
• Partner with Risk, Compliance, and Information Security to align analytics and AI practices with model risk management, privacy, cybersecurity, and consumer protection requirements.
• Ensure data integrity, accuracy, and completeness across critical reporting and decision-support systems.
• Oversee data architecture, data warehouse/lake, ETL/ELT pipelines, and analytics tooling across cloud and on-prem environments.
• Establish standards for responsible AI use, including bias monitoring, explainability, auditability, and appropriate-use controls.
• Manage analytics and AI vendors, platforms, and data providers, including due diligence, contract review, performance monitoring, and third-party risk coordination.
• Oversee enterprise change management and release controls for analytics models, reporting logic, and AI-enabled processes.
• Develop and report analytics program metrics, model performance indicators, and data quality KPIs to executive leadership.
• Support regulatory exams and internal/external audits involving data management, reporting accuracy, models, and AI usage.
• Manage departmental budget, staffing, and technology investments related to analytics and AI capabilities.
• Promote data literacy and analytics adoption across business units through training and stakeholder engagement.
  
  

Compliance

• Comply with all applicable regulations and Bank policies regarding employment and employment law.
• Participate in annual compliance and other job-related training.
• Comply with applicable banking regulations, Bank policies and procedures, and supervisory guidance related to data governance, model risk management, AI usage, and third-party risk management.
• Support regulatory exam, audit, and risk assessment activities related to analytics, reporting, and AI systems.
• Comply with Bank’s internal privacy and ethics standards.
  
  

Relationships And Contacts

• Internal: Frequent contact with executive leadership, risk management, finance, lending, operations, compliance, and technology teams to support analytics, reporting, and AI initiatives.
• External: Interaction with data analytics and AI vendors, data providers, consultants, auditors, and regulators.
  
  

Education And Experience

• Bachelor’s degree in Data Science, Analytics, Computer Science, Information Systems, Statistics, or related field. Master’s degree preferred.
• 10 years of experience in data analytics, business intelligence, data management, or data science roles, with at least 5 years in leadership.
• Experience in a regulated industry required; financial services or banking strongly preferred.
• Experience implementing enterprise analytics, BI, and AI/ML solutions in production environments.
  
  

Skills And Competencies

• Proven leadership in enterprise analytics, data governance, and AI program development.
• Strong knowledge of data architecture, data warehousing, BI platforms, and analytics tooling.
• Proficiency in SQL, Python/R, and data modeling.
• Experience with modern data platforms (Snowflake, Azure, AWS, Databricks, etc.).
• Strong familiarity with BI tools (Power BI, Tableau, Qlik).
• Experience with AI/ML lifecycle management and model governance practices.
• Demonstrated expertise in model risk management, data privacy, and AI risk considerations within regulated environments.
• Experience with cloud data and analytics platforms and modern data pipelines.
• Strong knowledge of data quality management and metadata management practices.
• Ability to translate business objectives into measurable analytics and AI solutions.
• Strong project management and vendor management skills.
• Familiarity with banking regulatory expectations affecting data, reporting, and models.
• Excellent written and verbal communication skills, including executive-level reporting.
• Strategic thinker with ability to translate business needs into technical solutions and a focus on controlled innovation and measurable business value.
• Collaborative and cross-functional leadership approach.
• Relevant certifications (e.g., CDMP, CBIP, PMP, cloud analytics certifications) are a plus.
  
  

Penn community Bank is an equal opportunity employer.