Senior Product Insights Analyst - Credit Card

Overview

Own product performance analytics for GoTyme Group's group-level credit card product, launching across the Philippines and South Africa, and build its analytical foundation from zero.

What you'll do

• Own end-to-end performance analytics covering activation, engagement, spend, repayment and retention across all markets.
• Track and interpret key KPIs including NPS, activation rates, digital adoption and unit economics (interchange, fee revenue, loyalty costs, ECL contribution), and translate findings into product and commercial storylines.
• Monitor portfolio health, including revolve rates, payment behaviour, limit utilisation and cohort evolution, with forward-looking commentary.
• Identify performance inflection points early and generate root-cause hypotheses.
• Analyse the full acquisition and onboarding funnel from application through activation and first spend, and size improvement opportunities.
• Embed in sprint ceremonies and product rituals, and define measurement frameworks for new features before they go live.
• Provide pre-launch data readiness checks and post-launch performance reads for every release.
• Support A/B testing and experiment design to evaluate product and go-to-market initiatives.
• Synthesise analysis into conclusions, flag strategic implications, and propose concrete product or commercial actions.
• Proactively surface insights on behavioural patterns, market signals and competitive benchmarks.
• Support go-to-market strategy, value proposition testing, and loyalty/rewards design with data-backed recommendations.
• Partner with in-country analytics and credit risk teams to validate and localise findings across the Philippines and South Africa.
• Build and maintain self-serve dashboards in Databricks and Mixpanel covering business performance, funnel health, portfolio trends and unit economics.
• Use AI tooling such as Claude, Cursor and Databricks AI to compress the time from question to answer.
• Contribute to analytics best practices, documentation and data quality standards across the Credit Card programme.

What you'll need

• Expert-level SQL, including complex queries, window functions and optimisation at scale.
• Proficiency in Python / PySpark for data manipulation, statistical analysis and automation.
• Experience with BI and visualisation tools: Databricks and Mixpanel (primary); Tableau or similar also acceptable.
• Knowledge of statistics, including hypothesis testing, cohort analysis and experimental design.
• Demonstrated daily use of AI tools to accelerate insight generation and automate workflows.
• 5+ years in data/analytics.
• Experience in financial services, fintech or banking.
• Lending domain experience (credit card, BNPL or personal loans), with revolve rate, vintage analysis and ECL contribution as familiar vocabulary.
• Experience with customer lifecycle analytics: acquisition, activation, engagement, retention and churn.
• Core competencies: end-to-end ownership from raw data to recommendation; insight, not just analysis; speed (good-enough-fast over perfect-and-late); proactivity; and data literacy leadership.

Nice to have

• Exposure to credit risk concepts (vintage analysis, ECL, delinquency) is a meaningful advantage.
• Bachelor's or Master's in Mathematics, Statistics, Economics, Computer Science or a related quantitative field.
• Experience in a multi-market or multi-country product environment.
• Familiarity with Visa/Mastercard reporting tools or card management system platforms.
• Background in high-growth startup or digital bank environments.

Details

• Reports directly to the Director of Product, with a dotted line to the Head of Data & Analytics.
• Locations: Ho Chi Minh City, Vietnam; Bengaluru, India.
• Work mode: Hybrid (HCMC-based), with flexibility to work from home or the office.
• Overseas travel opportunities to the Philippines, South Africa and group offices.