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Senior Product Insights Analyst - Credit Card

GoTymeX

Singapore, SGhybridPosted Jun 1, 2026

About the role

About GoTymeX

GoTymeX is the product, technology and data analytics hub of GoTyme Group. At GoTymeX, we're reimagining digital banking across emerging markets, across South Africa and Asia. Our mission is to unlock human potential, and we aim to do so through the development of transformative financial services that empower individuals and small businesses. We believe in the power of digital in building products that make a real difference in our customers' lives. Today, our products serve more than 22 million customers.

About the Credit Card Product

We are building a group-level credit card product — launching across the Philippines and South Africa — on a modern global stack. The analytical function at the heart of this programme has never existed before. We’re creating it now — and we’re looking for the person to build it from zero with us.

Where This Role Sits

You will report directly to the Director of Product, and work day-to-day alongside the Credit Card Product Owners, Engineers, Designers and Business Analysts. You will carry a dotted-line to the Head of Data & Analytics, giving you deep technical mentorship while remaining fully embedded in the product team. You will collaborate regularly with in-country data and credit risk analysts across the Philippines and South Africa.

Why Work with GoTymeX

Innovation-driven environment: Work with the latest technologies including Serverless aspects of AWS Cloud, AI-augmented engineering, microservices, Java, and Python

International and collaborative culture: Be part of a dynamic team that values collaboration, continuous learning, and personal growth

Competitive benefits: Enjoy a comprehensive benefits package, opportunities for professional development (see below) • Learning and development: Access to technical seminars, conferences, career talks, and overseas training to accelerate your career advancement and ensure continuous growth

Impactful work: Contribute to projects that directly influence financial empowerment and access in emerging markets

About This Role:

The Senior Product Insights Analyst is the analytical engine of this team, owning the narrative behind every product decision. This isn’t a reporting role. It’s a product intelligence function. You’ll build the analytical foundation for our credit card business, identify what’s working and what isn’t, and tell us — with confidence — what to do about it.

Key Responsibilities

Product & Business Performance

Own end-to-end performance analytics: activation, engagement, spend, repayment, and retention across all markets

Track and interpret key KPIs — NPS, activation rates, digital adoption, unit economics (interchange, fee revenue, loyalty costs, ECL contribution) — and translate findings into clear product and commercial storylines

Monitor portfolio health: revolve rates, payment behaviour, limit utilisation, and cohort evolution — with forward-looking commentary, not just snapshots

Identify performance inflection points early and generate root-cause hypotheses — don’t wait to be asked

Funnel, Onboarding & Product Development Lifecycle Support

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; 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 Insight Generation & Strategic Recommendations

Go beyond the numbers — synthesise analysis into conclusions, flag strategic implications, and propose concrete product or commercial actions

Proactively surface insights the team didn’t know to ask for: behavioural patterns, market signals, competitive benchmarks • Support go to market strategy, value proposition testing, and loyalty/rewards design with databacked recommendations

Partner with in-country analytics and credit risk teams to validate and localise findings across the Philippines and South Africa Dashboards, Tooling & AI Utilisation

Build and maintain self-serve dashboards in Databricks and Mixpanel covering business performance, funnel health, portfolio trends, and unit economics

You’ll use the best of modern AI tooling — Claude, Cursor, Databricks AI — to compress the time from question to answer. In our environment, fast insight beats slow perfection

Contribute to analytics best practices, documentation, and data quality standards across the Credit Card programme

Insight Generation & Strategic Recommendations

Go beyond the numbers — synthesise analysis into conclusions, flag strategic implications, and propose concrete product or commercial actions

Proactively surface insights the team didn’t know to ask for: behavioural patterns, market signals, competitive benchmarks • Support go to market strategy, value proposition testing, and loyalty/rewards design with databacked recommendations

Partner with in-country analytics and credit risk teams to validate and localise findings across the Philippines and South Africa Dashboards, Tooling & AI Utilisation

Build and maintain self-serve dashboards in Databricks and Mixpanel covering business performance, funnel health, portfolio trends, and unit economics

You’ll use the best of modern AI tooling — Claude, Cursor, Databricks AI — to compress the time from question to answer. In our environment, fast insight beats slow perfection

Contribute to analytics best practices, documentation, and data quality standards across the Credit Card programme

Requirements

Technical Skills

SQL: expert-level — complex queries, window functions, optimisation at scale

Python / PySpark: proficient for data manipulation, statistical analysis, and automation

BI / Visualisation: Databricks and Mixpanel (primary); Tableau or similar also acceptable

Statistics: hypothesis testing, cohort analysis, and experimental design

AI-augmented analytics: demonstrated daily use of AI tools to accelerate insight generation and automate workflows — this is an expectation, not a nice-to-have

Domain Experience

5+ years in data/analytics; financial services, fintech, or banking required

Lending domain strongly preferred — credit card, BNPL, or personal loans. Terms like revolve rate, vintage analysis, and ECL contribution should be second nature, not new vocabulary

Exposure to credit risk concepts (vintage analysis, ECL, delinquency) is a meaningful advantage

Experience with customer lifecycle analytics: acquisition, activation, engagement, retention, and churn

Core Competencies

End-to-end ownership: raw data to recommendation — accountable for whether it’s right

Insight, not just analysis: “here’s what the data shows, here’s what I think it means, here’s what I’d do” — every time

Speed: good-enough-fast beats perfect-and-late in a high-velocity build environment

Proactivity: you spot the question before it’s asked and flag the signal before it becomes a problem

Data literacy leadership: you raise the analytical bar of everyone around you — not just your own output

Preferred Qualifications

Bachelor’s or Master’s in Mathematics, Statistics, Economics, Computer Science, or 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

Benefits

Competitive salary that recognises your talent and potential

Performance-based bonus, including stock-based incentives for high performers

Conferences and expert-led training to accelerate your career

Flexibility to work from home or the office (HCMC-based, hybrid)

Generous annual leave allowance, paid birthday leave, and additional days off

Meal and parking allowances

Premium healthcare for you and your family

Overseas travel opportunities — Philippines, South Africa, and group offices

Questions about this role

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