Graduating with MS in Data Science, I am a persistent, hard-working, and passionate learner. Having won hackathons in AI and
machine learning, my core competency lies in solving problems pertaining to all verticals of retail, customer requirements through
careful statistical analysis, machine learning and business intelligence.
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Experience
O9 Solutions Inc – Software Engineer/Data Science (Dallas, Texas) May 2019- Aug 2019
● Utilized SQL Query to access client data and built Time series sales forecasting model using machine learning to forecast sales of 1000 unique products across all regions and customers for Bridgestone.
● Conducted exploratory data analysis, feature engineering, constructed lag features and achieved 20% improvement in forecast accuracy.
● Designed TABLEAU dashboards to provide findings and insights to VP and Managers.
Protector Security – Business Operations Analyst (Mumbai, India) July 2017 – June 2018
● Scripted advance SQL query on the ETL source and provided insights to managers using TABLEAU dashboards.
● Boosted the resource productivity levels of data validation team by coordinating with cross-functional teams to create SQL custom query suite for testing results data against different kinds of operational ETL reports developed by the BI team.
● Elevated human resource planning efficiency by 15% by building forecasting models to meet client’s requirements.
● Analyzed financial reports using advance excel to provide insights on operating expenses, revenue generated to stakeholders.
ITC Hotels- Data analyst (Mumbai, India) Feb 2017 - June 2017
● Analyzed key performance indicators using TABLEAU dashboards to empower business decisions.
● Performed customer segmentation and analyzed customer’s feedback reviews to build promotional strategies for pleasant customer experience that improved customer retention.
● Reduced reordering costs by 35% by creating explanatory models and maintaining Stock reports using historical data.
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Projects
M5 Forecasting Walmart (Kaggle Competition) Presently working
• Built machine learning Time series model to forecast the unit sales of various products sold in different states of US by Walmart.
• Constructed various lag features, implemented feature engineering, and added external calendar data to improve forecast accuracy.
Airbnb Zillow data Analysis March 2020
• Analyzed performance metrics such as break-even period, expected revenue, review ratings of the Airbnb listings to find the most profitable zip codes to make investments.
Machine Learning Implementation (Appliance Energy and Census dataset) Aug- Nov 2019
● Preprocessed data by applying Feature selection, feature transformation, Dimensionality reduction and clustering algorithms.
● Built ensemble methods, neural networks, gradient descent models and hyper tuned parameters by observing different learning curves.
Artificial Intelligence Hackathons
CBRE (1st prize winner): Nov 2018
● Built cost effective business test cases that leverage IOT/AI to help improve CRE attractiveness. Presented the work to the chief level executives of CBRE to incorporate the solutions in their projects.
SIGNAPAY (2nd Prize Winner): Visual description of the risk level of businesses for processing loans. Dec 2018
● Scraped reviews form yelp and google after basic validation performed sentimental analysis using NLP.
● Identified risk level with 90% precision and Created a visualization dashboard to show the risk patterns associated with companies