Behind The Team #11 | Data & Feature Engineering – A Key Part of Home Credit’s Risk Intelligence Foundation

Data & Feature Engineering – A Key Part of Home Credit’s Risk Intelligence Foundation

At Home Credit Vietnam, our Data & Feature Engineer team is one of the core enablers in powering risk decisions and shaping smarter financial solutions for millions of customers. By building robust data pipelines and unlocking features for advanced machine learning, the team ensures our models and engines run with accuracy, speed, and scale.

✨ 𝐀 𝐜𝐥𝐨𝐬𝐞𝐫 𝐥𝐨𝐨𝐤 𝐚𝐭 𝐭𝐡𝐞 𝐭𝐞𝐚𝐦’𝐬 𝐜𝐨𝐫𝐞 𝐟𝐨𝐜𝐮𝐬:
✅Building resilient data pipelines that power risk assessment, antifraud systems, underwriting, and credit decision engines with high-quality, real-time data.
✅Designing and refining ML features that boost the accuracy, scalability, and reliability of models in key business processes - from customer insights to payment advice.
✅Leveraging a powerful On-Premise data ecosystem built on Hadoop, Spark, Airflow, dbt, and Kafka - enabling large-scale data processing and actionable intelligence at speed.

🚀 𝐆𝐚𝐦𝐞-𝐂𝐡𝐚𝐧𝐠𝐞𝐫 𝐢𝐧 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 – 𝐇𝐨𝐦𝐞𝐌𝐋
One of the most impactful milestones of the Data & Feature Engineer team is HomeML - an in-house MLOps platform developed in collaboration with Underwriting, Anti-Fraud, Data Science, Payment Advisory, IT-Data Platform, IT-Data Product.

The platform enhances the way machine learning models are built and deployed by standardizing data, streamlining system operations, and improving overall model deployment efficiency at scale - further leading the implementation of an MLOps framework, streamlining end-to-end ML workflows - from data preparation and model development to deployment and monitoring - in close collaboration with our Data Scientists and IT department.

The team successfully deployed several machine learning models - all running seamlessly on our HomeML platform - driving faster, data-driven decisions and significantly enhancing underwriting accuracy, operational efficiency, and customer experience by using key demographic, behavioral, and credit data.

✅Real-time models strengthen risk control and fraud prevention using social, location, and behavioral insights.
✅Batch models (e.g., Promise-to-Buy, Card Churn, Client Segmentation) enable proactive customer engagement through predictive insights and personalized financial support.

💥What makes this project remarkable is the collaboration behind it - where the Data & Feature Engineer team joined forces with IT and business units to build a unified, data-driven ecosystem for smarter credit decisions. This collaboration reflects a shared commitment to innovation and impact - driving better customer experiences and promoting responsible financial inclusion.

👉Ready to make an impact with Data & Feature Engineering team today?