• Are you open to working remotely? Yes
  • Please Enter All Locations You Are Open to Work (each line will be each city, country location)
    United States
  • Allow Profile Promotion To Recruiters/Companies Yes
  • Allow Profile Promotion on Social Media Yes
  • Allow Profile Promotion to Alumni Yes
  • Viewed 494

About me


  • - Present
    University at Buffalo

    MS in Data Science

    ● GPA: 3.8/4.0 ● Coursework: Statistical Data Mining, Data Model & Query Language, Probability Theory, Predictive Analytics, Machine Learning, Reinforcement Learning. ● AWS Certified Cloud Practitioner

  • - 2017
    Indian Institute of Technology (IIT)

    Bachelor of Technology

    Achieved 99.76 Percentile in JEE (All India exam with 1.4 million candidates) for admission into IIT.


  • 2022 - Present
    The Perfect Child LLC,

    Data Analyst Intern

    ● Built an interactive maps application to match clients and Therapists, decreasing time and complexity of matching.
    ● Automated repetitive data collection from a dynamic website with Selenium, saving 30 minutes daily.
    ● Achieved synchronization while maintaining data segregation by combining individual google sheets files with Appscript to synchronize changes made in both the combined and individual sheets.
    ● Replacing a buggy software for logging therapy data, manually calculating billing hours for therapists by building a streamlined webapp hosted on AWS saving $5k/month for a small business, increasing efficiency, and gaining complete access to data.

  • 2019 - 2021

    Associate Data Scientist

    ● Engineered an Automated Valuation Model (AVM) using TensorFlow-based custom nearest-neighbor architecture to identify comparable properties by enriching core dataset from multiple sources, and lead a team of 3
    o Automated property valuation resulting in ~$25 million annual savings by decreasing ~2700 man hours weekly.
    o Built the SQL ETL pipeline to extract features for real estate properties from ~100 GB of OSM US maps data.
    o Collaborated with all stakeholders on biweekly calls to deploy the AVM on AWS SageMaker.
    o Reported iterative improvements, and insights for adding variables on client facing weekly calls.
    o Established Quality control checkpoints in the data pipeline prevent data inconsistencies and other issues.
    ● Developed a Demand forecast model with 1800 SKUs for a major European EV supplier.
    o Leveraged Time Series forecasting packages such as fb-prophet, neural prophet, & seq2seq neural nets.
    o Reduced time taken for forecasting from 1 week to 4 hours with an end to end pipeline.
    ● Optimized scheduling with a heuristic-based driver scheduling algorithm to incorporate business constraints.
    o Produced a simulation of bills movement across 34 terminals for a long-haul trucking client.
    o Removed human input for driver scheduling, optimizing time taken from multiple days to 15 minutes.
    ● Built Sales Forecast Model using Keras for creating business strategy for an American online clothing chain.
    ● Developed an end-to-end data pipeline on Azure utilizing Azure functions for daily scheduled ETL.