About the Company
Our client is a Singapore-headquartered B2B technology company operating at the intersection of SaaS, supply-chain digitization, and embedded finance. Our mission is to help SMEs across Southeast Asia run their operations more efficiently while leveraging proprietary business data to power smarter credit and cash-flow solutions with financial institution partners.
We are building the financial operating system for SMEs across the region, and data sits at the core of that ambition.
About the Role
We are looking for a Senior Data Analyst based in Malaysia to own the metrics, insights, and analytical foundations that guide product growth, lending performance, fraud monitoring, and future AI Engine development.
This is a hands-on role for someone who can move comfortably between business analytics, product intelligence, credit and fraud insights, and data enablement. You will help turn our proprietary operational data into sharper decisions today and scalable data assets for tomorrow.
What You'll Do
Business & Product Analytics
- Own core business and product KPIs across revenue, retention, activation, funnel conversion, and product usage
- Build dashboards and analyses to help teams understand customer behavior, growth opportunities, and operational friction
- Conduct cohort, segmentation, funnel, and behavioral analysis to support product and business decisions
- Partner with Product and Engineering to define event tracking and improve data capture
Fraud & Credit Analytics
- Build monitoring dashboards for fraud, repayment behavior, credit utilisation, delinquency, and portfolio performance
- Identify suspicious patterns, anomalies, and early warning signals across SME customers
- Prepare labelled datasets for fraud detection, credit scoring, and risk model development
- Define fraud signals, credit features, and risk indicators with Product, Engineering, and leadership
Data Foundations
- Maintain data dictionaries, metric definitions, and documentation for key tables, dashboards, and transformations
- Ensure consistency and accuracy across dashboards, reports, and recurring business metrics
- Work with Engineering to improve data quality, resolve data gaps, and strengthen analytical reliability
ML/AI Data Enablement
- Build feature tables and historical datasets for future AI Engine, fraud detection, and credit scoring use cases
- Support model evaluation, monitoring, and post-deployment performance analysis
- Translate operational, product, and lending data into usable features for AI-driven decisioning
- Co-create the above with the tech team by providing the essential logic while the tech team productizes it
What You Bring
Must-Have:
- 3-6 years of experience in data analytics, business intelligence, product analytics, or a related role
- Expert SQL skills, including complex joins, CTEs, window functions, and data validation
- Proficiency in dashboarding and BI tools such as Looker, Metabase, Power BI, or Tableau
- Ability to translate business questions into clear analytical approaches, metrics, and recommendations
- Strong communication skills, with the ability to explain insights clearly to technical and non-technical stakeholders
- Comfortable working independently with remote teams across Southeast Asia
Good-to-Have:
- Experience in fintech, lending, embedded finance, B2B SaaS, marketplaces, or SME-focused businesses
- Python programming skills for analysis, especially with pandas and NumPy
- Experience with product analytics tools such as Mixpanel, Amplitude, or GA4
- Exposure to fraud analytics, credit risk, repayment behavior, or loan performance data
- Familiarity with data quality checks, metric definitions, data dictionaries, and documentation
- Experience preparing datasets or features for machine learning, fraud detection, credit scoring, or AI products
Why Join Us
- High Impact: Work at the intersection of SaaS, supply-chain, and embedded finance
- Growth Opportunity: Be a foundational member of the data team in a high-growth tech company scaling across Southeast Asia
- Flexibility: Work independently with a remote-first team
