Biography
Completed my Masters in Data Science from University of British Columbia, Vancouver, where I designed, deployed, containerized various machine learning projects and applied statistical modelling concepts to solve problems in the world of Machine Learning and Data Science. Along with that, I am also an experienced Software Development Engineer. Interested in Machine Learning Engineer, Data scientist opportunities and looking forward to leveraging my diverse skill set to build solutions.
Download my resumé.
Interests
- Machine Learning
- Deep Learning
- Computer Vision
- Data Science
- Software Engineering
Education
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Masters in Data Science, 2022
University of British Columbia, Vancouver
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Bachelors in Computer Science and Engineering, 2019
Shiv Nadar University, India
Skills
R
Python
Statistics
Databases
Data Visualization
Cloud Computing
Machine Learning
Docker
Experience
Machine Learning Engineer, Capstone Project
- Designed and developed reproducible machine learning pipeline and modularized scripts to detect head collisions in sports videos using YOLOv5 and Resnet 3D algorithms
- This reproducible pipeline saved 60% of the time spent by humans in analyzing the sports videos manually
Software Engineer 2
Dell International Svc Pvt Ltd
- Led a team of 3 members and integrated the tool(QE Assistant) with CI/CD pipeline to determine performance bottlenecks before production stage, which reduced the number of production failures by 15% over the course of 18 months
- Mentored a college intern to help her build chatbot for the in-house performance testing tool(QE Assistant)
Software Engineer 1
Dell International Svc Pvt Ltd
- Designed and developed an in-house performance testing tool(QE Assistant) from scratch that enables QAs to schedule load tests, identifies performance bottlenecks in Dell web applications, shares customized test reports via email and analyses the quality of the test.
- This tool reduced time consumed in operational overhead by 40%. It is used by 65% of engineering projects in Dell
Big Data Intern
Birlasoft Pvt Ltd
- Performed Twitter Sentiment Analysis on FIFA World Cup tweets using Hive, Flume and Python
- Built a java library that is integrated in ETL pipelines across the team and is capable of migrating more than 1000 schemas from Oracle DB into a data warehouse (Hive) by bridging the gap between their schemas’ data types
Projects
Confirmation of head collisions in sports videos
Detection of occurrence of head collisions in sports videos using YOLO and 3DCNN algorithms. This would save 90% of the time spent manually in the analysis and detection of collisions in the entire game
Prediction of daily rainfall in Australia using cloud computing techniques
A Python package that makes data scientists’ job easier and saves time. It cleans the data, performs EDA and compares performance of the baseline model with basic Classification or Regression models
An R package that makes data scientists’ job easier and saves time. It cleans the data, performs EDA and compares performance of the baseline model with basic Classification or Regression models
A data science project that predicts the census income based on the demographic features using RandomForestClassifier.
An undergraduate project on ERP Data Mining and Analysis on university students’ data
This mini project was created as part of internship program for Twitter Sentiment analysis for the FIFA World Cup, 2018 related tweets.
Achievements
Women in Data Science Hackathon
- Ranked 1st in Vancouver and top 2% out of 829 (16/829) teams worldwide.
- Used ensemble modelling along with PCA and clustering techniques to predict the building energy consumption
Bot Detection model
- Ranked 6th among 40 teams in Dell.
- Used Naïve Bayes algorithm to classify the mouse movements as Bot or Human on Dell’s home page, based on mouse mapping technique
Prediction of MSP for Farmers
- Predicted MSP(Minimum Support Price) for the Indian Farmers using Linear Regression(0.83 R2score) which resulted in a job offer by Dell International Services