Retail Banking Analytics Manager

Citi is looking for a Retail Banking Analytics Manager to lead a high-performing team of data analysts within the Wealth Intelligence organization, reporting directly to the Head of Retail Performance Execution. In this role, you will harness advanced analytics to shape the strategic direction of Citi's US Retail Banking and Citigold business, turning complex data into clear business decisions that accelerate deposit, lending, and investment growth.

This is a senior leadership opportunity for an analytics professional who thrives at the intersection of data science, financial services, and executive-level influence.

• Lead a team of data analysts across multiple concurrent projects, setting priorities, managing deliverables, and maintaining accountability for outcomes.
• Champion the adoption of AI-driven approaches across the analytics team, setting the standard for how large-scale data challenges are approached and ensuring the team builds capability in emerging AI methodologies relevant to retail banking.
• Partner directly with senior leadership to translate advanced analytics into strategic recommendations that optimize coverage models and accelerate frontline performance.
• Analyze large, complex internal and external data sets to evaluate business strategies and measure the impact of key commercial decisions on deposit, lending, and investment growth.
• Design and implement data collection, processing, and cleaning workflows, applying statistical models, algorithms, and data visualization techniques to support exploratory and predictive analysis.
• Identify and compile data sets using tools (Python, SQL) to predict, improve, and quantify the success of business-to-business outcomes.
• Document data requirements and analytical findings in a manner that bridges technical execution and executive decision-making, ensuring insights are actionable at the leadership level.
• Assess risk implications of analytical outputs and business recommendations, ensuring decisions reflect sound judgment and adhere to applicable standards and regulatory requirements.
• Apply AI-powered tools and machine learning techniques as both a hands‑on contributor and team leader, embedding intelligent automation into analytical workflows to increase the speed and precision of business insights.

• 10 or more years of experience in analytics, financial or business analysis, or credit and risk analysis within financial services.
• Demonstrated ability to lead and develop analytical teams, including full people management responsibilities such as performance evaluation, hiring, and resource planning.
• Expert knowledge of advanced statistical techniques and the applied experience to use them in driving measurable business results. In-depth understanding of financial services business models, with the ability to connect analytical outputs to key commercial drivers.
• Practical experience leveraging AI and machine learning tools to solve real business problems, with the ability to contribute directly to AI-driven analysis as well as guide a team in applying these techniques effectively.
• Proficiency in data querying and compilation tools to extract and structure data sets for analysis at scale.
• Effective project planning and delivery management skills, with the ability to oversee multiple work streams and meet senior stakeholder expectations.
• Strong analytical thought leadership, with a track record of shaping strategy through data rather than simply reporting on it.
• Demonstrated ability to lead AI adoption within an analytics function, identifying where intelligent tooling creates measurable business value and translating that into team practice and deliverable outcomes.