Chief Data Officer

Location: Hybrid in NYC (Local only) Term: Full Time

The Chief Data Officer (CDO) is a newly elevated executive role responsible for shaping and executing Bank's enterprise data strategy. Reporting directly to the CEO, the CDO will build a data-driven culture across all business lines, with particular emphasis on the Bank's retail and private banking franchises. This leader will own the data governance framework, drive advanced analytics and AI capabilities, and ensure that data is a strategic asset that fuels client growth, operational efficiency, and regulatory confidence. This is a high-visibility, high-impact role suited for a banking executive who understands data not merely as a technical function, but as a business imperative and who brings credibility earned on the front lines of client-facing banking.

Candidates need to have recent Chief Data Officer (or equivalent title) experience or be ready to move into that type of role. Candidates must have good tenure and/or long projects. Candidates with recent local projects highly preferred. No relocation

• Define and drive Bank's multi-year data strategy, aligned to the Bank's business goals across retail, private banking, and commercial segments.
• Serve as the executive sponsor for all data transformation initiatives, partnering with business and technology leaders to ensure adoption and ROI.
• Establish a data-as-product mindset, making curated, trusted data accessible and actionable for decision-makers at all levels.

• Build and institutionalize a comprehensive data governance framework covering ownership, stewardship, lineage, quality standards, and lifecycle management.
• Partner with Compliance, Risk, and Legal to meet all regulatory data requirements including BSA/AML, FDIC, FFIEC, and NY DFS obligations.
• Implement data quality metrics, scorecards, and remediation workflows to continuously raise the standard of enterprise data assets.

• Champion the adoption of advanced analytics, machine learning, and AI to enhance client segmentation, personalization, credit decisioning, fraud detection, and cross-sell intelligence with a focus on retail and private banking use cases.
• Build and lead a high-performing team of data scientists, engineers, and analysts, cultivating talent and creating a center of excellence for data and analytics.
• Evaluate and implement modern data infrastructure including cloud platforms, data lakes, and BI tooling appropriate to the Bank's scale and risk profile.

• Act as a trusted strategic partner to the heads of Retail Banking and Private Banking, translating data insights into actionable business strategies that deepen client relationships and grow revenue.
• Work closely with Marketing to deploy data-driven client acquisition and retention campaigns tailored to Bank's affluent and institutional client base.
• Engage regularly with the Board and senior leadership to communicate data strategy, progress, and the value of data investments.

• Foster a data-literate organization by developing training programs, self-service analytics tools, and a culture of evidence-based decision-making.
• Lead change management efforts to shift mindsets from intuition-driven to insight-driven practices across all business units.

• 15+ years of progressive experience in banking or financial services, with substantial tenure in retail banking or private banking in a senior leadership capacity.
• Demonstrated track record of building or transforming data and analytics functions within a regulated financial institution.
• Deep understanding of retail and/or private banking products, client journeys, P&L dynamics, and the data that drives them.
• Experience establishing data governance frameworks and navigating bank regulatory environments (FFIEC, FDIC, NY DFS, BSA/AML).
• Strong executive presence with the ability to influence at the Board level and drive cross-functional alignment.
• Proven ability to build, mentor, and retain high-performing data teams.

• Prior CDO, Chief Analytics Officer, or equivalent executive data leadership title.
• Experience with cloud-based data platforms (AWS, Azure, or GCP) and modern data stack tooling (dbt, Snowflake, Databricks, or similar).
• Familiarity with AI/ML frameworks and experience governing the responsible use of AI in a banking context.
• Advanced degree (MBA, MS in Data Science, Statistics, or a related quantitative field) preferred.