Credit Data & Analytics Analyst

GoTyme PH (Philippines); Quezon City; On-site; PHP 420,000 - 800,000; Full time

Job summary

GoTyme Philippines is seeking a Credit Data & Reporting Analyst to support data processes for campaigns, regulatory reporting, and business insights. Fresh graduates or early‑career professionals who are detail‑oriented and analytical are encouraged to apply.

You will work with marketing, lending risk, analytics, and data engineering teams to ensure accurate reporting, reliable datasets, and AI‑assisted analytics workflows.

Qualifications

• Bachelor’s degree in data science, information systems, statistics, mathematics, finance, economics, or related field (must-have).
• Fresh graduates or up to 2 years of relevant experience acceptable.
• SQL basics to intermediate; Python a plus.
• Exposure to Databricks is advantageous.
• Familiarity with BI/visualization tools (Power BI, Tableau, Qlik, etc.).
• Strong analytical thinking and attention to detail.
• Good communication and collaboration across teams.
• Willingness to learn and grow in a fast-paced digital banking environment.

Responsibilities

• Assist in data extraction, transformation, and audience segmentation for campaigns and lifecycle initiatives.
• Support preparation of periodic regulatory and credit bureau reports with data validation and reconciliation.
• Design and maintain dashboards to monitor campaign performance, portfolio health, and credit risk KPIs.
• Collaborate with marketing, risk, analytics, and data engineering to ensure accurate, actionable insights.

Skills

SQL

Python

Data analysis

Attention to detail

Communication

Education

Bachelor’s degree in Data Science or related field

Tools

Databricks

Power BI

Tableau

Qlik

Job description

GoTyme Philippines is seeking a Credit Data & Reporting Analyst to support data processes for campaigns, regulatory reporting, and business insights. Fresh graduates or early‑career professionals who are detail‑oriented and analytical are encouraged to apply.

You will work with marketing, lending risk, analytics, and data engineering teams to ensure accurate reporting, reliable datasets, and AI‑assisted analytics workflows.