Lawrenceville, Georgia, United States
I am a Data Scientist and passionate about working with data. I leverage my background in programming, databases, big data technologies and data visualization to solve complex business problems. Skills: Python, Machine Learning, NLP, Deep Learning,R, R-shiny, Java, Spark, SQL, REST, Html/CSS ► Add me to your professional network◄
o Created and deployed data pipelines for IOT enabled kitchen appliances that brings the logs from AWS and other metadata through AWS API Gateway to Analysis Services Cube. Developed PowerBI dashboards for connected appliances which is used across the organization to gather valuable insights on appliance usage and app usage. o Provided continuous support on adhoc analysis on different subscription plans to measure its effectiveness. Created automated pipelines that brings the data from Chargebee to azure data‐lake through Chargebee APIs. o Developed Powerapps (Canvas apps) to help Operations team track the orders from 3PL carriers, 3PL carriers to manage schudling of delivery, Finance team to track their Budget, Marketing Team to track their promotional events in different regions, Business Team to reconcile orders across different platforms (D365, Salesforce, DataMasons, Payment Gateways). o Created Pipelines to send IOT event logs to CDP tools (MixPanel, BlueConic) for further analysis.
► Fantasy Hockey games Win Predictions using XGBoost Model. ► Worked on developing framework for attribute-based similarity to find most similar products. This is used for recommendation on the website as well as determining competitive/optimal prices. ► Brought in scraped competitor websites data to visualize the competition for similar skus in the market. Visualization is done in R shiny App. ►Developed R-shiny App in Logistics space to comprehensively visualize anomalies in the Freight cost charged to the customers by the carriers
► Worked on Aspect based Sentiment Analysis using Deep learning for predicting customer sentiments around the products's quality, Shipping experience and Customer Service experience. ► Used Neo4j to solve the optimal routing problem for products being shipped from Builddirect warehouses to customers ► Applied Hidden Markov Models to estimate the customer attributes like budget intent, color intent etc., based on the products he visits, which is then used to bias product recommendations on the website ► Worked on a collaboratively evolving algorithm and process for influencing the results ordering from search and navigation operations on website ► Developed Demand Forecasting models in python ► Did Google Trends Forecast for products in python ► Used Adobe Dynamic Tag Manager to track events on Builddirect website
► Researched and Implemented Clustering Algorithms and analysed the potential demand for new products ► Visualized the clusters over time by developing Shiny Application, a web framework for R ► Worked on different models for Demand Forecasting in R ► Used Tableau and d3.js to visualize data and outcome of analysis
► Requirement gathering from Financial Institutions and streamlining ► Developed RESTful WebServices that handles backend banking logic in Spring-Hibernate framework of Java ► Worked on UI (HTML/CSS and javascript/jquery) for Banking Web Applications