AI-Powered Credit Decisioning Systems Engineer

2 days ago

Bikaner, Rajasthan, India beBeeCredit Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
AI-Powered Credit Decisioning Systems Engineer

We're seeking a seasoned Machine Learning Engineer / Data Engineer to join our AI-driven credit lending platform team.

In this role, you'll design and deploy scalable ML solutions that power loan origination, decisioning, and management systems.

  • 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 regulatory requirements and integrate model explainability (XAI).
  • Optimize workflows for scalability, performance, and cost efficiency on Azure Cloud.

Requirements:

  • 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).

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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