• An Inquisitive Analyst with a passion for data, with demonstrated skills in Data mining, Visualization, Mathematics and Statistics.
• Master’s in Data Analytics from Northeastern University.
• Proficient in all aspects of Advance Excel, R, Python, SQL, ETL, PowerBI, Tableau and Qlik. Capable of preparing report and document, optimizing, visualizing and predicting data for business decisions.
• Collaboration, Communication combined with strong quantitative skills and analytical skills are some of my biggest strengths. Looking forward to leveraging quantitative and analytical knowledge to optimize data and create patterns for making business decisions.
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Experience
Marketing Data Analytics Intern at MathWorks:(Mar'20-Sep'20)
Developed reports and dashboards using tools like Microsoft PowerBI, Advance Excel which facilitate effective business analysis and provided efficient data driven decisions with end to end reporting solutions.
Provided monthly and quarterly analysis to the marketing team indicating performance of current strategies with opportunities for improvement and also provided advanced pricing analysis on the MOOC courses provided by MathWorks.
Analyzed customer data using Python and SQL and performed ad-hoc analysis requests to generate customer insights.
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Projects
Indian Premier League (IPL): ML Implementation
Analyzed team selection by grouping about 800 players into pools and visualizing player performances.
Applied K-Means Clustering algorithm to group players according to their proficiency of play.
Conducted Exploratory Data Analysis (EDA) and developed a model to show relationship between extra runs and winning
margin by using linear regression.
The UNICEF Child Mortality Rate:
Studied various country’s child mortality rate from various regions/parts of world and examine trends over years across globe.
Performed visualization of under five years child mortality rate for three specific countries Canada, Italy and Thailand to show trend of overall child mortality rate with Tableau.
Bike Sharing Rental system – Data Analysis and Data Visualization:
Prediction of bike rental count hourly or daily based on the environmental and seasonal settings.
Created interactive dashboards based on analysis and drafted data in a compelling way to enable data-driven storytelling.
Yelp Review Analysis – Data Mining
Discovered latent topics in positive and negative restaurant reviews from Yelp dataset by running LDA algorithm.
Estimated optical number of topics using Topic coherence score to obtain meaningful and interpretable results.
Developed Utilized Google Cloud Natural Language API to perform Sentiment Analysis of restaurant reviews.
MapReduce – Parallel Data Processing:
Found temperature variations of stations using different design patterns in MapReduce Framework on EMR.
Implemented Random Surfer Model using PageRank algorithm in MapReduce to rank Wikipedia articles.