Aspiring data scientist having more than 2+ years experience working on data science projects by developing prescriptive, descriptive, predictive solutions using analytical, statistical and machine learning strategies, with a result centric approach. Highly skilled in machine learning, data visualization and creative thinking.
• Programming Languages: Python | R | SQL | JavaScript
• Machine Learning Algorithms: Linear Regression | Logistic Regression | Random Forest | Decision
Tree | SVM | XG-Boost | K-means clustering | Neural Networks | RNN |CNN|
• Python Libraries: NUMPY │ SCIPY │ PANDAS │ MATPLOTLIB │ SEABORN │ BOKEH │ PLOTLY │ SCIKIT-LEARN │ TENSORFLOW KERAS │ NLTK
• Statistical Techniques: t-test | Chi-Square Test | Correlation | Hypothesis Testing
• Tools: Tableau| Python | R Studio | WEKA | Jupyternotebook |Power BI | Microsoft Azure | Advanced MS Excel | Matlab
• Data Infrastructure: Hadoop | Hive | HDFS | MySQL | NoSQL
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Experience
PROFESSIONAL EXPERINECE
Catholic Relief Services Jan 2020 - Present
Data Science Co-op (Capstone Project)
Baltimore, MD
• Built a Random Forest, XG-Boost, Support Vector Machine and Neural Networks machine learning models to predict the
redemption rate of bed nets for the Benin region. Predicted 90% redemption rate of net cards which will help the CRS team to
conduct the bed net distribution program more effectively.
• One of my main tasks is data wrangling and performing data visualizations using Power BI and loading the machine
learning models in the Power BI software which will help in conveying the results effectively to the leadership.
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Alcon, A Novartis division May 2019 - Aug 2019
Data Science Intern
Fort Worth, TX
• Built a K-NN, Stochastic Gradient boosting and Light GBM machine learning model to classify the different research grants.
• Generated tableau dashboards, tools, and templates to communicate findings to the leadership.
• Automated the Adhoc report generation with selenium tool using python program which can generate 100+ reports in a day.
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George Mason University – School of Business Aug 2018 - May 2019
Graduate Research Assistant Fairfax, VA
• Developed a web crawler to retrieve articles from Factiva website using python programming.
• Project on tree census data to determine the best predictors of a tree’s health to maintain healthier urban forest.
• deployed algorithms like SGB, Naïve Bayes, K-NN, RF and SVM. The SGB model performed the best for this dataset
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Projects
Predicting Boston Housing Prices with Machine Learning Algorithm:
• Developed linear regression model to predict the monetary value for the houses located in Boston area.
• To evaluate the model’s performance, employed randomsearchCV technique for hyperparameter tuning.
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Marketing campaign for a grocery store using Tableau:
• I analyzed the data from different grocery stores to mainly study the different marketing campaign strategies
• Performed data visualizations in tableau explaining how the marketing campaign influenced the customers.
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Marketing customer value analysis project using R Studio, Tableau and MySQL:
• The main aim of this project is to analyze the behavioral pattern of customers by analyzing their purchasing patterns.
• Mainly used R programming in analyzing the sale of products by developing statistical models.