
Highly Skilled Data Scientist and Machine Learning Engineer
2 weeks ago
Key Responsibilities:
- Design, develop, and deploy credit scoring and risk assessment models using classification, regression, and alternative data models.
- Build and optimize end-to-end data pipelines on Microsoft Azure for structured and semi-structured financial/telco data.
- Implement model monitoring, retraining frameworks, and governance workflows to ensure compliance with regulatory requirements and integrate model explainability.
- Develop APIs and microservices for seamless integration with LOS, LMS, and external systems, leveraging MLOps best practices.
Required Skills & Experience:
- 5+ years of professional experience in Machine Learning, Data Engineering, or related fields.
- Strong proficiency in Azure Cloud services, including Azure ML, Azure Data Factory, Databricks, Synapse, and Cosmos DB.
- Hands-on experience with big data tools and a solid understanding of data governance, security, and compliance in financial services.
Benefits:
- Opportunity to work on cutting-edge AI-driven credit lending platform projects.
- Remote-friendly role with flexibility to work from anywhere, with potential opportunity to relocate onsite based on project and business needs.
Preferred Qualifications:
- Prior experience working with banks, fintechs, or telcos in credit/lending solutions.
- Knowledge of explainable AI techniques and exposure to big data tools.
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