Karan Naik

Software Engineer /
Data Analyst

Skills

    Big Data Analysis

    Data Visualization

    Data Mining

    Data Scraping

    Data Warehousing

    Microsoft Office

Languages

    Python

    Javascript

    R

    SQL

    SPSS

    C/C++

    HTML

    CSS

    Bash

    SAS

Frameworks / Modules

    Hadoop

    Hive

    Flask

    React.js

    MySQL

    Chartio

    Excel

    Preso

    Node.js

    Linux/Unix

    Git

    Tableau

    PostgreSQL

    SQLite

Services

    Heroku

    AWS

    Google Analytics

Experience

Data Engineer - Senior Analyst

May 2018 - Present
Avanade
Client:
  • Developed critical data ingestion and processing pipelines built with Python across client’s hardware analytics data infrastructure
  • Worked closely with Data Scientists and Data Engineers to help optimize compute resources and design a better data warehousing infrastructure while enforcing data governance
  • Built and maintained high visibility dashboards for VP level stakeholders in Tableau and proprietary dashboarding tooling pertaining to hardware health and hardware operational performance within client’s on-prem Data Centers
  • Established high-level data pipeline design documentation and worked closely with proprietary ETL tooling to provide on-call support
  • Leveraged pre-existing tooling on top of Hadoop, SQL, Python, Hive, and Presto to help drive further business value

Data Analyst

Oct 2017 - March 2018
Curology
  • Built dashboards and data visualizations in Chartio and SQL to report on Operations and Marketing KPIs
  • Assisted in global customer lifetime value modeling and customer acquisition cost modeling
  • Led market research analysis that provided valuable insights towards product development and customer acquisition strategy
  • Performed statistical AB testing on ad content and placement that effectively reduced customer acquisition cost by 50%

Software Development Coach

Aug 2017 - Present
theCoderSchool
  • Taught a curriculum focused on client-side and server-side web development using Python, Javascript, HTML, and CSS
  • Covered material ranging from types, methods, and data structures to security, web services, and APIs

Data Engineer Intern

Jun 2016 - March 2017
Omaze

       Software Engineering

  • Architected proprietary data analysis tools with Flask and Angular.js that helped derive actionable product strategy from customer acquisition data
  • Created RESTful API endpoints in Flask for data analysis toolsets that interacted with MySQL databases and Amazon Web Services
  • Created data visualizations using D3.js displaying customer acquisition trends

       Data Analysis

  • Deployed functional and cosmetic AB tests and analyzed subsequent data from Apache Spark cluster using Scala and Python
  • Generated ad hoc reports on KPI and KPA from MySQL data
  • Resolved discrepancies and redundancies in data pipeline to expedite ETL processes

Projects

Engineering

Minirl - minirl.com
  • Built a URL shortening service using React.js, Flask, and SQLite and deployed to Heroku
  • Designed and implemented a custom encryption algorithm that minimized collisions and retaining robustness in use cases
  • Wireframed vital components and developed styles that contributed to a user-centered design (UCD)
Byteschool - TBA
  • Developing a software engineering education platform focused on building high school engineering talent
Albumify -
  • Created a shell client which searches and extracts m4a files corresponding to a track and artist name from YouTube
  • Functionality includes ability to extract a complete album if provided additional file with track names
BoulderBlast -
  • Created a graphics based game where a player must navigate through a maze, avoid robots, and collect jewels

Data Analysis

Los Angeles Fire Department Kaggle Contest
  • Awarded first place in Data Mining course's Kaggle competition for predicting Los Angeles Fire Department response time accurately
  • Developed a data cleaning and feature engineering schema that accurately trained models and lowered testing errors 12 percent more than other groups
  • Developed, tuned, and cross-validated regression and tree based models including linear regression, random forest, and gradient boosting (xgboost) models
  • Explored ensembling of many different weak learners to minimize standardized residual errors
UCLA Datafest (Expedia)
  • Led exploratory analysis of repeat hotel customer behavior in the United States via Expedia
  • Unearthed trends pertaining to importance of chain tendency and devised a marketing plan focused on improving customer loyalty
  • Developed random forest models to determine feature importance and devised actionable product strategy emphasizing those features
Capstone Project (NCAA Football)
  • Consulted for a NCAA Football team on whether biometric practice data influenced game time performance
  • Revealed nuanced behaviors of performance by player positioning and analyzed trends over the course of a season
  • Scraped ESPN for football player statistics

Education

Statistics, B.S

Graduated March 2017
University of California, Los Angeles