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4 days ago
About this role, we are seeking a skilled Machine Learning Engineer to lead our efforts in scaling ML products and credit risk policy.
This position will involve ensuring APIs operate smoothly at scale, identifying ways to simplify and reduce customer journey risks. The ideal candidate will have an entrepreneurial mindset, cloud-based tools for automation and encryption, and expertise in APIs.
About the Team:
You will be part of our fast-paced ML Engineering Team within the Digital Banking Unit. This team works closely with data engineers, data scientists, product managers, and senior stakeholders to drive innovation and growth.
Required Skills and Qualifications- Masters or Undergraduate degree in Computer Science/Electrical/Civil/Mechanical.
- 6-8 years of industry experience, with at least 3-4 years in Machine Learning (ML)/MLOps or Business Rule Engine (BRE) implementation.
- End-to-end ML/MLOps system architecture, including model/BRE implementation, debugging, and production maintenance.
- Proficient in Python, PySpark, NumPy, Pandas, SQL, and Linux.
- Hands-on experience with Azure cloud services, including Azure Databricks, Spark, Data Warehousing, and pipeline orchestration.
- Skilled in Azure DevOps for CI/CD pipeline setup and management.
- Exposure to credit risk modeling and financial services is a strong plus.
- Excellent communication and stakeholder management.
- Strong project management and cross-functional collaboration abilities.
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