Data Analyst - Banking

• Query clean, and prepare datasets to support predictive model development.
• Perform data profiling, outlier analysis, missing value treatment, and variable selection.
• Generate statistical summaries, histograms, distributions, and correlations to support model assumptions
• Assist in feature engineering with code (Python, SQL) based pipelines.
• Develop intemal data validation and sanity checks to support model input/output reliability.

• Advanced SQL and scripting for large-scale data extraction and transformation
• Strong in Python for data analysis (Pandas, matplotlib, seaborn).
• Experience using Jupyter notebooks, Git, and shared model/analytics repos
• Comfort working with transactiorial, behavioral, and log-based data
• Self-directed and technical; works off specifications from data science lead or product owner
• No need to present to business users or interpret commercial outcomes
• Focus on clean, efficient code, reproducibility, and high data integrity

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