About Shashank Gupta
With 3 years of professional experience in data analytics and an ongoing graduate degree in Business Analytics at Clark University, I’m pursuing my career in the data analytics domain. I’ve always been passionate about using data to solve real-world problems. I am also a good storyteller to build up a story based on the insights in the data using data visualization techniques and other required tools.
I have completed my summer internship at Coresight Research, Inc., where I worked as a data analyst intern and worked on location and web analytics using Python and Tableau. I am currently continuing my internship in this organization for the fall semester.
Academically, I have worked on multiple data science projects like classification of Mashable article’s popularity score using logistic regression and random forest classification, predicting the transaction pattern based on online shopping user behavior using logistic regression, K- Nearest Neighbor (KNN), and Support Vector Machine (SVM) using python and Tableau. Currently, I am pursuing the course Advance Big Data Analytics where I am learning big data technologies like Hadoop, Apache Spark, and NoSQL. I also have a strong GPA of 3.83 / 4.00 in my graduate education.
I have always been passionate about solving problems using data to find any solution and would like to assure you that I can work on solving the problems that your organization might be dealing from years. I would request you to please let me showcase my skills and technologies that I have learnt in years from my undergraduate to graduate education along with 3 years of industrial experience. Key Responsibilities: Extract and analyze data to develop models, gather requirements, identify KPI’s, draw Insights, recommendations and share them with clients and stakeholders. Skills and area of expertise:
Proficient in extracting and preparing structured, unstructured and semi-structured data for analyses using Python, and SQL.
Data Engineering Skills: Working on learning Big Data technologies like Hadoop, Apache Spark and NoSQL.
Business Intelligence Engineering Skills: Proficient in BI tools like Tableau, KNIME, Power BI, etc…
Machine Learning Skills: Supervised Learning (Regression, Decision Tree, Random Forest, Gradient Boosting, SVM, KNN), Unsupervised Learning (Clustering, PCA), Time series.
Statistical Skills: Perform various statistical testing methods and employ testing processes such as hypothesis testing, correlation and co-variance, significance testing using P-values, t-tests etc.
Python and Database: Data Analysis, Modeling, Visualization tools, and web scraping (Pandas, Matplotlib, Seaborn, Scikit-learn, XGBoost, BeautifulSoup, Request) and SQL Server, MySQL and MongoDB.
Strong quantitative and analytical skills balanced with a business perspective
Excellent communication skills, written and verbal; ability to present results in a clear & concise manner.