Data Scientist

We are seeking a motivated Data Scientist – Banking Domain to support analytics, predictive modeling, and data-driven decision-making for banking and financial services initiatives. This role focuses on analyzing customer, account, transaction, payment, lending, and risk-related data to identify trends, build models, and support business insights.

• Analyze banking and financial services data including customer, account, transaction, payment, lending, and credit data
• Write SQL queries to extract, clean, transform, and validate datasets from multiple sources
• Use Python for data analysis, feature engineering, statistical analysis, and basic machine learning models
• Support development of predictive models for customer behavior, risk analysis, fraud detection, churn, loan performance, and campaign effectiveness
• Perform exploratory data analysis to identify trends, patterns, anomalies, and business insights
• Build and validate datasets used for reporting, dashboards, and model development
• Collaborate with business analysts, data engineers, BI teams, and stakeholders to understand business problems and data needs
• Create visualizations and reports to communicate insights to technical and non-technical audiences
• Support data quality checks, outlier analysis, missing value handling, and model validation activities
• Maintain documentation for data sources, assumptions, model logic, analysis results, and business recommendations

• 2–3 years of experience in data science, analytics, data analysis, or related roles
• Strong SQL skills for querying, joining, aggregating, and validating data
• Good Python knowledge using libraries such as Pandas, Num Py, Scikit-learn, Matplotlib, or similar tools
• Understanding of statistical analysis, data cleaning, feature engineering, and machine learning basics
• Experience with exploratory data analysis, trend analysis, and business insight generation
• Basic understanding of banking, financial services, payments, lending, risk, or customer analytics is preferred
• Exposure to cloud platforms such as AWS, Azure, or similar environments is a plus
• Understanding of data warehousing, data pipelines, and structured datasets
• Strong analytical mindset with attention to data accuracy and business context
• Good communication skills and ability to explain data insights clearly to business stakeholders