Hi,
I'm Kabir Chaturvedi

I'm a

Seeking Full-Time Opportunities in the Data Science Domain | MS Data Science @ IUB | Data Science Internships at eBay & Azirio | Data Analyst at NTT Data | Expertise in Data Science, Analysis, ML, Deep Learning, Cloud and AI.

About Me

Data Scientist

Greetings! I’m Kabir Chaturvedi, a Master's student in Data Science at Indiana University Bloomington. I have hands-on experience as a Data Science Intern at eBay and Azirio, and as a Data Analyst at NTT Data. I specialize in leveraging technologies like Python, Spark, SQL, Power BI, and Azure Data Factory to transform complex datasets into actionable insights, optimizing business outcomes. I am currently seeking full-time opportunities in the data science domain to apply my skills and contribute to impactful projects.

Experience

May, 2024 - Aug, 2024

Data Science Intern - eBay

  • Assessed two large company data tables on the Zeta platform using Spark SQL queries to quantify the impact of Promoted Listings on the Ads Platform
  • Architected efficient SQL and Spark notebooks to extract, transform, and aggregate 10 billion-row Parquet datasets for Promoted Ads Campaigns, reducing data processing time by 63% and enhancing computational efficiency by 170%.

Jan, 2024 - May, 2024

Data Science Intern - Azirio

  • Crafted customized PowerBI dashboards based on client consultations, achieving an 11% rise in sales and enhancing customer retention by 4%
  • Created an automated Azure Data Factory workflow to handle CRM ID extraction and database updates; saved 8 hours monthly of manual work.
  • Innovated SQL query algorithms to categorize 8,000+ user email IDs into corporate or franchise segments; bolstered data organization and improved reporting accuracy, leading to a 25% reduction in data processing time.

Dec, 2022 - May, 2023

Data Analyst Intern - NTT Data

  • Conducted a comprehensive performance analysis of the Indian payments industry, using Excel, PowerBI, and PowerPoint to create visualizations that improved senior management decision-making by 12%.
  • Analyzed over 100,000 daily transaction records with advanced Excel techniques, including pivot tables and VLOOKUP, to deliver insights that reduced customer support incidents by 20% and enhanced operational efficiency.

Education

2023 - 2025

Master of Science in Data Science - Indiana University Bloomington

CGPA - 3.834

Relevant Courses: Applied Machine Learning, Data Mining, Statistics, Information Visualization, Social Media Mining, Applied Database Technologies

2019 - 2023

Bachelor of Science in Data Science - NMIMS

Grade - 3.51

Relevant Courses: Machine Learning, Deep Learning, Database Management, Big Data Analytics, Advanced Mathematics, Statistical Methods, Natural Language Processing, Predictive Modelling, Business Visualization, Computer Vision, Artificial intelligence

Tech Stack

Languages and Databases

  • Python, R, SQL, MySQL, PostgreSQL, MongoDB, Snowflake, Flask

Data Visualization

  • PowerBI, Tableau, Gephi

Machine Learning / AI

  • NLP, LLMs, Deep Learning, TensorFlow, NumPy, Pandas, Computer Vision, Azure
  • Statistics, Machine Learning, Neural Networks, EDA, Apache Spark
  • Recommendation Systems, ETL, Keras, Transformers, ChatGPT-4, Reinforcement Learning

Latest Projects

AI Shakespeare NLP Driven Text Generation

AI Shakespeare NLP-Driven Text Generation

Utilizing NLP and deep learning to generate text in the style of William Shakespeare. Based on LSTM neural networks.

Telco Customer Churn Analysis

Telco Customer Churn Analysis

Predicting customer churn for a telecommunications company using supervised machine learning techniques.

Amazon Product Comparator

Amazon Product Comparator

A tool designed to revolutionize the way consumers engage with e-commerce by enabling efficient product comparisons on Amazon.

Visual Analytics of the Meta Kaggle Dataset

Visual Analytics of the Meta Kaggle Dataset

Comprehensive analysis of the Meta-Kaggle dataset to explore trends within the Kaggle community.

Social Media Mining

Social Media Mining

Research proposals and papers detailing analyses on various topics using data from social media APIs and sentiment analysis.