
Adept professional with extensive operations experience and “adept,” “capable,” “receptive,” “retain information,” and “able to quickly grasp new concepts.”
Python
Descriptive Analytics
Predictive Analytics
Seaborn
Matplotlib
Classification and Regression Algorithms
Exploratory Data Analysis
Clustering Techniques
Principal Component Analysis
Hyperparameter Tuning
Scikitlearn
Numpy
Pandas
Jupyter Notebook
Google Office Suite
Jira
Data Pre-processing
Machine Learning
Project 1: Unsupervised Learning
“Trade&Ahead”
Description: Analyzed financial stock data, grouped company stocks based on various attributes, and shared insights into the characteristics of each group in an effort to improve long-term investing decisions.
Skills: EDA, Kmeans Clustering, Hierarchical Clustering, Cluster Profiling
Project 2: Classification
“ExtraaLearn”
Description: Developed a model to identify which leads are more likely to convert to paid customers, and identified the factors driving the lead conversion process.
Skills: EDA, Data Pre-processing, Logistic regression, Multicollinearity, AUC-ROC curve, Decision trees, Pruning
Project 3: Ensemble Techniques and Model Tuning
“EasyVisa”
Description: Analyzed various Visa applications and built a predictive model to facilitate the process of visa approvals. Optimized the model to produce accurate predictions, and developed profiles for applicants that should be certified and those that should be denied.
Skills: EDA, Customer Profiling, Bagging Classifiers, Hyperparameter Tuning