I am a homecook turned data nerd.

In the past, I used to be a cooking fanatic (check out some of my recipes here: recipe site).

Nowadays, I excel in translating complex data into digestible business insights. In my projects and studies, I have applied traditional analysis methods as well as latest Machine Learning powered analysis methods to study elements such as company financials, company Annual Reports and CEO Pitches. Now, I look to help my teams/clients reform data streams and identify relevances from data all to make impactful decisions.


About

I grew up in India but my family and I migrated to America when I was 13. After 4 years, 3 states and 5 high schools, we finally found financial/familial stability in the Greater Houston area. In 2017, I joined TAMU for my Bachelor's in Computer Science and a minor in Statistics. Finally, I moved to NYC to join the MSCS program at Columbia University under the Machine Learning Track.

Skills

Languages:

  • Python
  • JavaScript
  • C++
  • SQL

    • Data Handling:

  • Python Libraries (scikit-learn, TensorFlow, Pandas)
  • RStudio/R Libraries (Dplyr, ggplot2)
  • Hadoop
  • PHP

    • Data Modeling:

  • Tableau
  • Power BI
  • Svg - JavaScript

    • Other:

  • MS Office (Excel, PowerPoint)
  • Agile SDLC
  • React
  • AWS cloud
  • Matlab

    • Projects

    Columbia University

    The Steve Jobs Effect (on CEO Product Pitches) - Class Project
    08/22 - 12/22

    Investigated plonology/language-use in consumer product pitches by CEOs through automatic speech recoginition models.

    Texas A&M University

    SMAC Tracker - Class Project
    01/20 - 05/20

    Developed (as a team) a Google Chrome extension that tracks user social media using React-JS and Bootstrap-JS. Used Knockout UI and Chrome API for front-end to show analytics in real-time.

    IIT Gandhinagar

    Summer Research Intern
    05/19 - 07/19

    Improved efficiency of raw MFCC vectors clustering by factorizing signals using bi-directional-RNN and Tensor Decomposition (NTD) to create Music Recommendation System with 62% accuracy.

    Texas A&M University

    ARP (Software Engineering Team)
    01/18 - 06/18

    Empirically tested (as a team) practicality of 5 code documentation practices in C++. Designed and Proctored the study for 20 participants. Check out the news article on our work here.


    Brown Institute/KFAI Project

    For a special project collaboration with Knight First Amendment Institute, we are Brown Institute created this React App Website aimed at educating folks on the inner-workings of social media recommendation algorithms.


    Machine learning for Climate Project

    For my upper level graduate course at Columbia on applying the ML/AI to aide in fight against global warming, I created a model that predicts the best off-shore wind farm configuration using publically available data from the NOAA.


    MIR Walkthrough

    Here is a short video I made in my undergrad AI course related to my project at IIT Gandhinagar internship.



    NBA International Player Network Graph

    Here is a NBA international player roster data visual I created in my Data Visualization course at Columbia University. You can interact with the year slider or the graph itself to view more information. Data Scraped from www.basketball-reference.com. Original Report: link.



    Shareholder Letter NLP-based Analysis

    Here are boxplots from my course project in my Empirical Data Science course at Columbia University. The visual shows characteristics of letters released by NASDAQ-100 companies between 2016 and 2018. You can interact with the select menu or the graph itself to view letter information (ticker and year of release).

    Resume

    Hobbies

    I enjoy running and cooking!

    Sahil Patel
    spatel16300@gmail.com