
Data Scientist/ml Engineer
3 weeks ago
In this role, you'll design and deploy scalable ML solutions that power loan origination, decisioning, and management systems.
You'll work on end-to-end data pipelines, model development, and integration with leading banking and fintech systems hosted on Microsoft Azure.???? Key Responsibilities:Design, develop, and deploy credit scoring and risk assessment models (classification, regression, alternative data models).Build scalable ETL/ELT pipelines on Microsoft Azure for structured and semi-structured financial/telco data.Implement model monitoring, retraining frameworks, and governance workflows.Develop APIs and microservices for seamless integration with LOS, LMS, and external systems.Collaborate with 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:5+ years of professional experience in Machine Learning, Data Engineering, or related fields.Strong programming skills in Python, Py Spark, SQL with experience in ML frameworks (scikit-learn, Tensor Flow, Py Torch).Proficiency in Azure ML, Azure Data Factory, Databricks, Synapse, Cosmos DB (or equivalent cloud tools).Hands-on experience with credit risk modeling, fraud detection, or financial ML models.Knowledge of API design and integration (REST/Graph QL).Familiarity with MLOps best practices (CI/CD, monitoring, retraining pipelines).Strong understanding of data governance, security, and compliance in financial services. Preferred Qualifications:Prior experience with banks, fintechs, or telcos in credit/lending solutions.Knowledge of explainable AI (XAI) techniques.Exposure to big data tools (Hadoop, Spark, Kafka, Trino/Presto).Bachelor's/Master's/Ph D in Computer Science, Data Science, or related fields.???? Work Location & Flexibility:Remote-friendly role with flexibility to work from anywhere.Opportunity to relocate onsite based on project and business needs.
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