BENYAMIN RAJ DUGGI

• Analyzed unstructured statistics from App Store and Google Play to create data-driven recommendations for successful app profiles.
  
  Data quality was ensured by automated cleaning and descriptive analysis utilizing Jupyter Notebook and Python modules such as Pandas, Numpy, and Seaborn.
  • Concluded that creating an app based on a well-known book may be beneficial for both markets.
  • Converted historical data into business insights using Python and SQL, proposing strategies to boost product sales.(Product Analytics)
• Monitored data quality and analyzed quantitative and qualitative data to understand product performance, customer behavior, and trends. Provided analytical and business solutions to market products to the appropriate customers at the right time.
  
  • Created interactive dashboards in Tableau to communicate insights, report KPI, analyze results, and propose strategic solutions.
  • Utilized Natural Language Processing tools and Scikit-learn from Python to assess customer satisfaction with Advanced Driver Assistance Systems.
  • Analyzed sentiment in customer reviews to understand their true impression of each system.
  • Developed dynamic dashboards in Tableau to highlight key characteristics influencing customer evaluations, including positive, negative, and neutral.
• Analyzed the NOAA Storm Database over the past decade to find the most detrimental occurrences to population health and economics.
  
  Exploratory analysis was performed using R statistical charts, including histograms and box plots, to identify trends and insights.
  • Visualized statistics and concluded that tornadoes are the most detrimental to population health, whereas floods cause the most economic damage.
  • Analyzed the National Emissions Inventory database from 2003-2013 to assess fine particle pollution in the US.

We validated, profiled, audited, and cleansed data

before identifying pollution-causing elements and trends for each individual across time using R charts like Line Plots and Bar Plots.

• Created a Dashboard to summarize results, concluding that overall emissions from PM2.5, coal combustion, motor vehicle sources, and industries reduced over a 10-year period.

WORD PREDICTOR 11/2020 -02/2021

Developed a predictive text model with a UI that predicts the next word based on user input. Trained the model on over 110 million words (600 Mb of text data) and used the "n-gram model with Backoff" algorithm to create a Shiny Web App in RStudio.

UNIFINDER : 05/2019-04/2020

Unifinder is a web application that connects colleges to user profiles based on various factors, developed in collaboration with seven students using an Agile system.

• Used PHP and JavaScript to develop the front-end and MySQL for the database.
As the Product Owner, I acted as a liaison between customers and the development team, facilitating decision-making and representing the product.
• Document user stories, specs, and product features in a thorough work order to guarantee team communication and compliance with necessary standards.
• Designed the Business Relationship Model to better understand inter-business operations and create fruitful relationships with partners.