Erdaus Ideris Email & Phone Number

Malaysia

Work on over $300 M loss forecast, responsible for developing and maintaining ARIMA and Holt’s Winter prediction models on car collections forecast project to improve the original accuracy by 20% while mitigating risk in decision making by leveraging data science• Designed general retention models and simple retention models by conducting over 300 million clients’ data to calculate customer lifetime value. Use insight gained from model to forecast the value of each customer and make… Show more Work on over $300 M loss forecast, responsible for developing and maintaining ARIMA and Holt’s Winter prediction models on car collections forecast project to improve the original accuracy by 20% while mitigating risk in decision making by leveraging data science• Designed general retention models and simple retention models by conducting over 300 million clients’ data to calculate customer lifetime value. Use insight gained from model to forecast the value of each customer and make customer segmentation• Implemented User Interfaces by using Tkinker to ensure active cooperation with business team and generate the pull-through of insights Show less

Worked on data cleaning and ensured data quality, consistency, integrity using Pandas, Numpy • Participated in feature engineering such as feature intersection generation; feature normalize and label encoding with Scikit-learn preprocessing• Performed data pre-processing tasks like merging, sorting, finding outliers, missing value imputation, data normalization, making it ready for statistical analysis• Used Pandas, NumPy, Scikit-learn in Python for developing various machine… Show more Worked on data cleaning and ensured data quality, consistency, integrity using Pandas, Numpy • Participated in feature engineering such as feature intersection generation; feature normalize and label encoding with Scikit-learn preprocessing• Performed data pre-processing tasks like merging, sorting, finding outliers, missing value imputation, data normalization, making it ready for statistical analysis• Used Pandas, NumPy, Scikit-learn in Python for developing various machine learning models such Decision Tree and Random Forest Show less