
Data Analyst
2 weeks ago
We're Hiring: Data Analyst (Credit Analytics | Remote | Full-Time)
Leverage financial and credit data to power AI-driven lending solutions
We are seeking a skilled Data Analyst (Credit Analytics) with 4+ years of experience to join our AI-driven lending platform team. In this role, you will analyze financial, customer, and transaction datasets, generate insights to support credit decisioning models, and deliver data-driven solutions across loan origination (LOS), loan management (LMS), and credit scoring systems.
Key Responsibilities:
- Collect, clean, and analyze structured and unstructured data (banking, fintech, telco usage, credit bureau).
- Collaborate with ML engineers to define features, validate models, and benchmark credit decisioning outputs.
- Develop dashboards and reports on loan performance, portfolio risk, customer segmentation, and key KPIs.
- Conduct exploratory data analysis (EDA) to identify gaps, biases, and enrichment opportunities in training datasets.
- Support regulatory compliance reporting by preparing summaries, documentation, and explainability insights.
- Contribute to data quality frameworks, governance standards, and lineage tracking.
Required Skills & Experience:
- 4+ years of experience in data analysis, preferably in credit/financial analytics.
- Proficiency in Spark-SQL, SQL, Excel, and BI/visualization tools (Power BI, Tableau, Superset, or equivalent).
- Strong analytical mindset with the ability to interpret financial/credit datasets.
- Hands-on experience with Python or R for data wrangling, EDA, and statistical analysis.
- Familiarity with Microsoft Azure data stack (Data Factory, Synapse, Databricks).
- Solid understanding of credit risk KPIs, NPA ratios, loan portfolio analysis, and financial modeling.
Preferred Qualifications:
- Experience in banking, fintech, or telco credit operations.
- Exposure to predictive modeling, customer segmentation, or fraud analytics.
- Knowledge of compliance frameworks (Basel, IFRS9, PDPA, GDPR).
- Bachelor's/Master's in Statistics, Economics, Finance, Data Science, or related fields.
Work Location & Flexibility:
- Remote-friendly role with flexibility to work from anywhere.
- Opportunity to relocate onsite depending on project and business needs.
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