Data Analyst, Financial Services

Role Overview

• Analyze customer, transaction, merchant, and agent data to identify trends, opportunities, and performance drivers across Wallets, Payments, Bill Payments, Merchant Payments, P2P Transfers, and other Financial Services products.
• Partner with Product Managers, Operations, Risk, Finance, and Engineering teams to answer business questions through data and support product decision-making.
• Develop and maintain dashboards, reports, and KPI tracking frameworks to monitor customer growth, engagement, retention, transaction performance, and revenue metrics.
• Conduct deep-dive analyses on customer behavior, payment funnels, wallet activation, transaction success rates, merchant activity, and agent performance.
• Support product discovery and feature development by identifying customer pain points, behavioral patterns, and growth opportunities using data.
• Design, execute, and evaluate A/B tests, feature launches, promotional campaigns, and product experiments to measure impact and guide future improvements.
• Work closely with Data Science and Risk teams to support customer segmentation, fraud monitoring, credit risk analysis, and predictive modeling initiatives.
• Perform exploratory data analysis (EDA) to uncover actionable insights and support the development of data-driven product enhancements.
• Monitor data quality, identify anomalies, and collaborate with Data Engineering teams to improve tracking, instrumentation, and reporting accuracy.
• Communicate findings and recommendations clearly to both technical and non-technical stakeholders through presentations, reports, and dashboards.

Requirements

• 2–5 years of experience in Product Analytics, Business Analytics, Data Analytics, or a related analytical role.
• Strong SQL skills and practical experience working with large-scale customer and transaction datasets.
• Proficiency in Python for data analysis, statistical modeling, and data visualization.
• Experience working with digital products, preferably within Fintech, Payments, Wallets, Banking, Lending, or Financial Services.
• Solid understanding of statistics, hypothesis testing, experimentation, and data-driven decision-making.
• Experience building dashboards and reports using BI tools such as Looker Studio, Looker, Tableau, or Power BI.
• Ability to translate business questions into analytical approaches and communicate insights effectively to stakeholders.
• Familiarity with cloud-based data platforms, preferably Google Cloud Platform (GCP) and BigQuery.
• Strong problem-solving, analytical thinking, and attention to detail.
• Excellent written and verbal communication skills in English.

Tech Stack

• BigQuery
• Cloud
• Google Cloud Platform
• Python
• SQL
• Tableau