Senior Manager – Data Analytics – Banking

Senior Manager – Data Analytics – Banking

Requirements

• 10+ years of experience in data analytics, preferably in fintech, banking, or customer-centric industries.
• 3+ years of experience managing and leading analytics teams and strategies.
• Strong proficiency in SQL and Python for data analysis and automation.
• Strong hands-on experience in managing multiple analytical workstreams.
• Proficient in designing, analyzing, and interpreting experiments.
• Well-versed in customer segmentation and deep-dive behavioral analytics.
• Proven ability to uncover revenue and growth opportunities through data insights.
• Track record of improving customer conversion and retention through data-driven product strategies.
• Experience in rolling out new products/features and tracking their impact.
• Skilled in developing compelling dashboards and reports to communicate insights effectively.
• Strong cross-functional collaboration with Product, Marketing, Finance, and Engineering teams.
• Advanced analytics capabilities, including statistical inference, significance testing, and forecasting methods.
• Exposure to machine learning modeling and related workflows.

Responsibilities

• Lead and mentor a team of data analysts, fostering a culture of analytical excellence.
• Devise and implement analytics strategies to enhance banking performance, revenue, and customer growth.
• Create and manage data pipelines, dashboards, and reports to track key performance indicators (KPIs) for the Banking team and ensure efficient dissemination of the KPIs.
• Deliver timely insights, identify key business performance drivers, and uncover untapped growth opportunities.
• Enable the development and implementation of new customer treatment models, incentives, and pricing strategies to optimize P&L growth.
• Conduct in-depth analyses using internal and third-party data to identify trends, discover opportunities, and elevate customer experience.
• Partner with stakeholders across Leadership, Product, Credit Risk and Engineering teams to define success metrics, analyze trends, and provide actionable recommendations.
• Partner with cross-functional teams, including Product, Engineering, Risk, and Customer Success, to conceptualize and launch new products and features.
• Design and Implement Experiments, customer segmentation, and personalization strategies and help establish frameworks and improve key processes.
• Review analytics initiatives on the banking and cross-functional teams and provide actionable feedback and recommendations.
• Deliver actionable insights to senior leadership on banking performance and key initiatives.
• Collaborate with Finance on business case analysis, revenue forecasting, and customer growth projections.
• Uphold data integrity, accuracy, and governance across the banking analytics ecosystem.
• Effectively manage team resources and personal bandwidth to prioritize and deliver high-quality analytical projects.

Preferred Qualifications

• Experience in fintech or financial services.
• Background in B2C products and analytics.
• Familiarity with credit, loans, or liquidity products.
• Experience in building classification and regression machine learning models.
• Strong knowledge of marketing data analytics, attribution, and performance measurement.
• Expertise in designing and analyzing randomized control trials (A/B or multivariate testing).