We’re Hiring : Machine Learning Engineer / Data Scientist (Full-Time, Onsite)
Build AI-powered credit decisioning systems on Microsoft Azure
About the Role
We’re looking for a Machine Learning Engineer / Data Engineer with 3+ years of experience to join our AI-driven credit lending platform team.
In this role, you’ll design and deploy scalable ML solutions that power loan origination, credit decisioning, and portfolio management systems.
You’ll work on end-to-end data pipelines, model development, and integrations with leading banking and fintech systems hosted on Microsoft Azure.
This is a full-time onsite position, offering hands-on collaboration with our data science, engineering, and product teams to shape next-generation credit intelligence solutions.
Key Responsibilities
- Design, develop, and deploy credit scoring and risk assessment models (classification, regression, alternative data).
- Build scalable ETL / ELT pipelines on Microsoft Azure for financial and telco datasets.
- Implement model monitoring, retraining frameworks, and governance workflows.
- Develop APIs and microservices for integration with LOS, LMS, and external systems.
- Collaborate with data analysts and product owners to translate business rules into ML / AI-driven logic.
- Ensure compliance with Basel III, GDPR, PDPA, and integrate model explainability (XAI).
- Optimize workflows for scalability, performance, and cost efficiency on Azure Cloud.
✅ Required Skills & Experience
3+ years of experience in Machine Learning, Data Engineering, or related fields.Strong programming skills in Python, PySpark, SQL with experience in ML frameworks (scikit-learn, TensorFlow, PyTorch).Hands-on experience with Azure ML, Data Factory, Databricks, Synapse, Cosmos DB (or equivalent cloud tools).Experience in credit risk modeling, fraud detection, or financial ML models.Knowledge of API design and integration (REST / GraphQL).Familiarity with MLOps practices (CI / CD, model monitoring, retraining pipelines).Strong understanding of data governance, security, and compliance in financial services.⭐ Preferred Qualifications
Experience working in banking, fintech, or telco environments.Knowledge of Explainable AI (XAI) and regulatory frameworks (Basel, IFRS9, GDPR, PDPA).Exposure to big data tools (Hadoop, Spark, Kafka, Trino / Presto).Bachelor’s / Master’s / PhD in Computer Science, Data Science, or related field.Work Location & Flexibility
Onsite role with opportunities for collaboration across cross-functional teams.Potential for future mobility or relocation within the organization.Employment Type : Full-Time