Job Purpose

The Business Intelligence Analyst Digital Products is responsible for driving commercial and product performance insights across the digital banking portfolio. This role focuses on analyzing customer behavior, product adoption, revenue generation and campaign effectiveness. By deeply exploring transaction data, the analyst will identify customer segments, predict product churn and uncover opportunities to maximize the lifetime value of digital banking products, providing the core insights needed by product managers to optimize their roadmaps.

Principle Responsibilities

• Monitor and report on key product metrics including transaction value/volume, fee revenue, margin analysis and monthly active product users.
• Evaluate the performance of specific digital products (e.g., Merchant Payments, Utility bill payments, Transfers etc.) against targets and historical trends.
• Analyze the direct revenue and cost structures of digital products to identify low-performing features or high-margin growth opportunities.
• Segment the digital banking customer base based on transaction frequency, product cross-holdings and value tiering to identify usage patterns.
• Track product dormancy and build analytical views to help identify customers at risk of abandoning specific digital services.
• Partner with marketing and product growth teams to measure the Return on Investment (ROI) and customer uptake of product promotions and feature rollouts.
• Design and maintain commercial, business-facing dashboards (using Power BI, Tableau or any other relevant tool) that give Product Owners a clear view of product health and customer trends.
• Work under the BI Manager to ensure commercial metrics (e.g., "Active Merchants", "Revenues per User") are modelled accurately and consistently from the raw data warehouse layers.
• Conduct deep-dive analyses to answer specific commercial questions, such as "Why are merchant payments dropping in a specific sub-segment?"
• Package internal product usage data to support business development teams when establishing partnerships with corporate merchants or fintech integrators

Qualifications Required

• Bachelors degree in Finance, Economics, Statistics, Data Science, Actuarial Science, or a related quantitative commercial field.
• Minimum of 3 years of experience in data analytics, financial analysis, or commercial BI, with a strong preference for experience in Retail Banking, Mobile Money, Fintech, or E-Commerce.
• Strong capability in writing SQL queries to extract, aggregate, and join complex transaction data tables and customer profile records.
• Minimum of 2 years of experience designing insightful, business-oriented dashboards in Power BI, Tableau, or Metabase, with advanced skills in data manipulation and rapid spreadsheet modeling for quick commercial lookups.
• Strong working knowledge of Python (Pandas/NumPy) or R for cohort analysis, customer segmentation, and statistical modeling.
• Ability to see past the raw numbers to understand the business impact, customer pain points, and financial drivers behind data trends, with exceptional capability to translate complex behavioral data into simple visual charts and highly actionable business recommendations.
• Comfortable embedding with non-technical Product Managers to understand their goals and proactively supply the data they need.
• Flexible and adaptive to market dynamics and experimentation, with a customer-centric mindset.

• Monitor and report on key product metrics including transaction value/volume, fee revenue, margin analysis and monthly active product users.
• Evaluate the performance of specific digital products (e.g., Merchant Payments, Utility bill payments, Transfers etc.) against targets and historical trends.
• Analyze the direct revenue and cost structures of digital products to identify low-performing features or high-margin growth opportunities.
• Segment the digital banking customer base based on transaction frequency, product cross-holdings and value tiering to identify usage patterns.
• Track product dormancy and build analytical views to help identify customers at risk of abandoning specific digital services.
• Partner with marketing and product growth teams to measure the Return on Investment (ROI) and customer uptake of product promotions and feature rollouts.
• Design and maintain commercial, business-facing dashboards (using Power BI, Tableau or any other relevant tool) that give Product Owners a clear view of product health and customer trends.
• Work under the BI Manager to ensure commercial metrics (e.g., "Active Merchants", "Revenues per User") are modelled accurately and consistently from the raw data warehouse layers.
• Conduct deep-dive analyses to answer specific commercial questions, such as "Why are merchant payments dropping in a specific sub-segment?"
• Package internal product usage data to support business development teams when establishing partnerships with corporate merchants or fintech integrators

• SQL
• Power BI
• Tableau
• Metabase
• Python (Pandas/NumPy)
• R
• Data Analysis
• Financial Analysis
• Commercial BI
• Cohort Analysis
• Customer Segmentation
• Statistical Modeling
• Data Visualization
• Business Acumen
• Communication
• Problem-solving
• Adaptability
• Customer-centricity

• Bachelors degree in Finance, Economics, Statistics, Data Science, Actuarial Science, or a related quantitative commercial field.
• Minimum of 3 years of experience in data analytics, financial analysis, or commercial BI, with a strong preference for experience in Retail Banking, Mobile Money, Fintech, or E-Commerce.
• Strong capability in writing SQL queries to extract, aggregate, and join complex transaction data tables and customer profile records.
• Minimum of 2 years of experience designing insightful, business-oriented dashboards in Power BI, Tableau, or Metabase, with advanced skills in data manipulation and rapid spreadsheet modeling for quick commercial lookups.
• Strong working knowledge of Python (Pandas/NumPy) or R for cohort analysis, customer segmentation, and statistical modeling.
• Ability to see past the raw numbers to understand the business impact, customer pain points, and financial drivers behind data trends, with exceptional capability to translate complex behavioral data into simple visual charts and highly actionable business recommendations.
• Comfortable embedding with non-technical Product Managers to understand their goals and proactively supply the data they need.
• Flexible and adaptive to market dynamics and experimentation, with a customer-centric mindset.