Description

You will build and deploy predictive models to solve complex banking challenges using large-scale datasets.

Responsibilities

• Perform exploratory data analysis on banking datasets to identify patterns and business opportunities.
• Build and validate predictive models using regression, classification, and clustering for credit scoring, fraud detection, and customer segmentation.
• Develop data pipelines and ETL processes using Azure Data Factory to prepare structured and unstructured data.
• Deploy models to Azure Machine Learning Service and implement MLOps practices for lifecycle management and monitoring.
• Collaborate with data engineers and stakeholders to translate business needs into production-ready data science solutions.

Required Skills

• 5+ years of experience in data science roles.
• Proficiency in Python and machine learning libraries such as SciKit-Learn and TensorFlow.
• Strong SQL skills with experience in Azure SQL Database or Azure Cosmos DB.
• Experience with Azure Synapse Analytics and Power BI for reporting and dashboarding.
• Solid understanding of statistical analysis, predictive modeling, and time-series forecasting.
• Experience with deep learning and NLP techniques.
• Hands-on experience with Azure Data Factory for feature engineering and data transformation.
• Bachelor's degree in Computer Science.

Preferred Skills

• Knowledge of Artificial Intelligence and AWS.

Key Skills

Education

Bachelor's degree in Computer Science