SAI SHARAN REDDY MANNE

A Data Science enthusiast wishing to expand my knowledge of AI and ML. With my experience in the past, I am able to work in any condition and will be working based on your requirements. A qualified business intelligence analyst is versed in data mapping and user acceptance testing to solve complex problems in high-pressure environments. Activates strong analytical skills to investigate trends in large amounts of data and formulate conclusions based on findings. Excels at cultivating, managing, and leveraging client relationships to foster extended engagements and business opportunities.

• Google Data Analytics
• Python for Data Science, AI & Development

Seminar presentation on "REPT: Reverse Debugging of Failures in Deployed Software".

Home Credit Default Risk, Spearheaded data preprocessing and cleaning efforts using SQL and Pandas, ensuring data integrity and reliability for subsequent analysis. Developed and implemented machine learning models to assess and predict default risk in home credit transactions, leading to a substantial decrease in loan defaults. Conducted exploratory data analysis (EDA) to uncover insights and trends within the financial datasets related to home credit, facilitating data-driven decision-making for risk management. Utilized Python to create predictive models, optimizing credit scoring systems specific to home credit, and enhancing overall lending strategies for improved risk assessment. Santander Customer Transaction Prediction, Spearheaded data preprocessing and cleaning efforts using SQL and Pandas, ensuring data integrity and reliability for subsequent analysis. Developed and implemented machine learning models to predict customer transactions for Santander, resulting in enhanced transaction forecasting accuracy. Conducted exploratory data analysis (EDA) to reveal patterns and trends within the financial datasets, enabling data-driven decision-making for optimizing customer transaction strategies. Utilized Python to create predictive models, improving the precision of transaction prediction and aiding in the development of targeted customer engagement strategies. IEEE-CIS Fraud Detection, Spearheaded data preprocessing and cleaning efforts using SQL and Pandas, ensuring data integrity and reliability for subsequent analysis in the context of IEEE-CIS fraud detection. Developed and implemented advanced machine learning models to detect and prevent fraudulent activities within IEEE-CIS transactions, leading to a significant reduction in fraud incidents. Conducted exploratory data analysis (EDA) to uncover patterns and trends within the datasets, facilitating data-driven decision-making for more effective fraud detection strategies. Utilized Python to create predictive models, optimizing fraud detection systems and improving the overall security of IEEE-CIS transactions.