About the company

SariPay is one of Southeast Asia's fastest-growing fintech companies focused on MSME financing and payments. Originally a fintech spin-off from Series C-funded B2B platform GrowSari, SariPay now stands independently (Saripay has its own financing and fintech companies regulated by SEC and BSP), delivering digital lending, payments, and embedded finance solutions to over 300,000 sari-sari stores and micro-entrepreneurs in the Philippines. The fintech business is growing 1.7x year on year and is profitable.

Overview

We are looking for a Data Scientist to join our Credit Risk team, supporting the development and monitoring of credit scoring models for SariPay's MSME lending portfolio. This role is ideal for someone early in their credit risk career who wants hands-on ownership of models that directly impact lending decisions for over 300,000 sari-sari store owners and micro-entrepreneurs.

Responsibilities

Analyze loan performance, customer behavior, and repayment data to identify risk patterns and portfolio trends.
Build and maintain statistical/ML models for credit scoring, default prediction, and portfolio risk assessment, under guidance from senior team members.
Develop dashboards and regular reports to track credit risk KPIs and portfolio health for stakeholders.
Support A/B tests on credit policy changes and lending criteria adjustments.
Write and maintain SQL queries for data extraction and validation; partner with Data Engineering on data pipeline needs.
Present findings and recommendations to internal stakeholders in clear, non-technical terms.

Qualifications

Must-have:

Minimum 3 years of experience as a Data Scientist, Credit Risk Analyst, or similar analytical role.
Working knowledge of statistical analysis and machine learning techniques (e.g., logistic regression, decision trees, gradient boosting) applied to risk or scoring use cases.
Proficiency in SQL and at least one programming language commonly used for modeling (Python or R).
Strong analytical and communication skills, with ability to explain technical findings to non-technical audiences.

Nice-to-have:

Experience in fintech, digital lending, banking, or telco credit scoring.
Exposure to credit scorecard development or portfolio risk analytics.
Experience deploying ML models into production environments.

Headquarters: 16th Floor, Century Spire Office Bldg., Poblacion, Makati City

Work Set-Up: At least 2x a week onsite

Senior Data Scientist - Credit Risk (Hybrid Work Set-Up)