●       Accumulated 5 years of industrial experience in Data Analysis, covering Data Mining, Statistical Inference, A/B testing, Machine Learning, Data Visualization, and ETL data pipelines.

●       Proficient in SQL, particularly MySQL and MS SQL Server, adept at crafting stored procedures, triggers, and complex queries for report generation and analysis.

●       Developed 12 dashboards for reporting and guided decision-making processes for stakeholders.

●       Utilized Python scripting throughout the data science project lifecycle, including data acquisition, cleaning, exploration, and modeling using Pandas and Scikit-learn libraries.

●       Possess a strong understanding of Retail Banking, with hands-on experience in statistical analysis, causal inference, statistical modeling, and machine learning, along with expertise in cloud platforms, NoSQL databases, ETL pipelines, and Shell Scripting.