Business Intelligence Analyst (AI) - Credit Product

What you'll do

• Partner closely with Credit / Retail Finance stakeholders across product, operations, promotion, and collection teams to understand business problems, define analytical approaches, and deliver actionable insights.
• Support data analysis and performance tracking across Credit business areas, including user conversion funnels, A/B testing, campaign performance, CRM engagement, collection performance, product journeys, and customer segmentation.
• Contribute to BI work for upcoming AI initiatives such as Promotion AI CRM, and Collection AI Chatbot by defining success metrics, experiment frameworks, monitoring dashboards, and post-launch performance reviews.
• Consolidate data from multiple sources, including business systems, marketing data, operational data, product behavior logs, and data warehouse tables, to build integrated datasets, reports, and dashboards for decision-making.
• Build, maintain, and enhance BI reports, Data Studio dashboards, Google Sheets analysis templates, and management reporting tools with clear metric definitions and reliable refresh logic.
• Critically evaluate business metrics and data quality, including metric definitions, date windows, partition logic, join granularity, funnel attribution, duplication risks, and abnormal trends.
• Improve internal processes through automation, reusable analysis templates, data validation workflows, and AI-assisted BI workflows to increase team productivity and reporting accuracy.
• Collaborate with data engineering, product, and tech teams to improve data marts, tracking design, data pipelines, and scalable analytics solutions.

Requirements

• Bachelor’s degree or above in Computer Science, Data Science, Statistics, Mathematics, Business Analytics, Information Technology, Finance / Banking, or related fields.
• Min. 1 year of experience in data analytics, business intelligence, data product, data engineering, or related roles.
• Strong SQL skills, with hands-on ability to work on complex data extraction, joins, aggregations, window functions, funnel analysis, and data validation. Python experience for data analysis or automation is required.
• Familiarity with at least one BI or visualization tool, such as Data Studio, Tableau, Power BI, Looker, Superset, or Google Sheets.
• Strong business sense and analytical thinking, with the ability to translate business questions into clear metrics, structured analysis, and practical recommendations.
• Detail-oriented and data-quality minded, with the ability to proactively validate metric definitions, sample logic, date windows, join granularity, and outliers.
• Able to work effectively with cross-functional teams in a fast-paced environment, with strong communication skills and ownership.
• Experience in finance, banking, consumer finance, credit, payments, risk, CRM, collection, growth marketing, or A/B testing is a plus.
• Experience with AI products, GenAI tools, AI chatbots, intelligent marketing, analytics automation, or LLM-assisted data workflows is a plus.