Munzor Hasan Minto

• · Participated in all phases of data mining, data cleaning, data collection, developing models, validation, and visualization
• · Accomplished data pipeline process, collected required data from different sources and converted into structured form using SQL
• · Hands on experience in Working with the large volume of data .
• · Incorporated Exploratory Data Analysis to identify the correlation between variables, multicollinearity, and hidden patterns, trends and seasonality using Numpy and Pandas libraries to perform data analysis
• · Analyzed customer churn distribution over the different attributes such as tenure, different services a customer has signed up for and demographic data using visualization libraries matplotlib and seaborn in python
• · Performed PCA, backward feature selection, correlation analysis for Dimensionality Reduction of the data to achieve the accuracy in the results
• · Performed SMOTE analysis to deal with unbalanced distribution of the data over the training data set
• · Implemented various classification models such as Logistic Regression, Decision Trees, Random Forest, KNN, XGBoost, and SVM and applied most efficient algorithm to predict the results
• · Performed K-Fold cross-validation to test models with different batches to optimize the model and prevent overfitting
• · Participated in feature engineering such as feature generating, PCA, feature normalization and label encoding with Scikit-learn preprocessing
• · Achieved 90% customer monthly retention by predicting the likelihood of returning customers using a logistic regression model in R
• · Designed and implemented end-to-end systems for Data Analytics and Automation, integrating custom visualization tools using R, Tableau, and Power BI

· Cleaned and manipulated complex datasets to create the data foundation for further analysis and the development of key insights (MS SQL server, R, Tableau, Excel)

· Incorporated various machine learning algorithms and advanced statistical analysis like decision trees, regression models, SVM, clustering using scikit-learn package in Python

· Worked on data pre-processing and cleaning the data to perform feature engineering and performed data imputation techniques for the missing values in the dataset using Python

· Performed Exploratory Data Analysis (EDA) to visualize through various plots and graphs using matplotlib and seaborn library of python, and to understand and discover the patterns on the Data, understanding correlation in the features using heatmap, performed hypothesis testing to check significance of the features

· Developed analytical approaches to answer high-level questions and provided insightful recommendations

· Conducted various statistical analysis like linear regression.

· Involved in extracting customer's Big Data from various data sources (Excel, Flat Files, Oracle, SQL Server, MongoDB, Teradata, and also log data from servers) into Hadoop HDFS

· Used pandas, numpy, seaborn, scipy, matplotlib, scikit-learn in Python for developing various machine learning algorithms

· Assured data quality and data integrity, and optimized data collection procedures on a weekly and monthly basis

· Created Data Quality Scripts using SQL and Hive to validate successful data load and assured the quality of data.

· Worked on different data formats such as JSON, XML, CSV, .dat and exported the data into data visualization/ ETL platform

· Evaluated model performance using techniques like R square, adjusted R square, confusion matrix, AUC, ROC curve, Root mean squared error etc.

· Incorporated, Developed and applied metrics and prototypes that could be used to drive business decisions

· Participated in ongoing research, and evaluation of new technologies and analytical solutions to optimize the model performance

· Used problem-solving skills to find and correct the data problems, applied statistical methods to adjust and project results when necessary

· Worked across cross-functional teams to understand the data requirements and provided the detailed analytical reports to accomplish the business decisions