Data Scientist

19 hours ago

Bengaluru Karnataka India, Karnataka Quant-data.io Full time

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

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