Bhavya Pandya

I'm

About

As a dedicated data science enthusiast, I have a deep interest in the field of machine learning and artificial intelligence. Through comprehensive exposure to the underlying concepts and their application in various projects, I have developed a love for data science. My passion lies in building and applying algorithms to solve real-world industry problems using the power of data.

Birthday: October 1999
Phone: +1 4803709761

City: Tempe, AZ
Email: bhavyapandya1610@gmail.com

Interests

Deep Learning

Machine Learning

Computer Vision

Natural Language Processing

Data Engineering

Visualization

Algorithms

Image Processing

Education

MS in Data Science, Analytics and Engineering

August 2023 - May 2025

GPA: 4.0/4.0

Relevant Coursework

Data Processing at Scale
Statistics for Data Analyst
Data Mining
Data Analytics (Using R)
Data Driven Optimization
Analyzing Big Data
Data Visualization
Project Management
Information Assurance and Security

B.E. in Computer Engineering

August 2018 - May 2022

GPA: 9.2/10.0

Relevant Coursework

Artificial Intelligence
Machine Learning
Big Data Analytics
Advance Calculus
Discrete Mathematics
Probability & Statistics
Advance Data Structures and Algorithms
Database Management Systems
Web Data Management

Industry Experience

Elite Ecom

October 2024 - January 2025

Data Science Intern

Analysed and interpreted complex datasets from TikTok shop platform, uncovering key marketing analytics and sales trends that led to a 25% improvement in campaign targeting efficiency.
Developed and implemented predictive models using Python and scikit-learn to forecast sales trends, achieving 85% accuracy in revenue projections and enabling data-driven inventory decisions.
Engineered automated data cleaning pipelines that processed over 100,000 daily TikTok shop transactions, reducing data preparation time by 40% and improving data reliability.
Created dynamic Tableau dashboards visualizing web traffic patterns and product performance metrics, leading to actionable insights that increased customer engagement by 30% on the TikTok shop platform.

Amsafe Aviation

June 2024 - August 2024

Business Systems Data Analyst Intern

Spearheaded data standardization initiatives across QAD ERP system, resulting in 40% reduction in cross-departmental data discrepancies and enhanced operational efficiency.
Engineered custom real-time reporting dashboards for senior management, streamlining decision-making processes & reducing report generation time by 60%.
Orchestrated implementation of data validation protocols across manufacturing and supply chain modules, leading to 90% improvement in inventory accuracy.
Designed and executed comprehensive data management training programs for cross-functional teams, achieving 100% adoption rate of new standardized processes across departments.

Thunderbird School of Global Management, Arizona State University

February 2024 - September 2024

AI Integration Specialist

Created an interactive negotiation simulation platform using OpenAI and Google Gemini, enabling real-world practice & personalized scenarios for students.
Implemented real-time performance feedback and analysed user data to enhance educational outcomes and user experience.
Built Conversational AI with Meta Human character, enabling communication with 7 animated characters.

Feynn Labs Pvt. Ltd.

April 2023 - June 2023

Machine Learning Intern

Developed and implemented machine learning models to analyze large datasets related to consumer behavior and market trends, contributing to data-driven decision-making and improving market strategy.
Conducted data cleaning and preprocessing, model selection and tuning, and visualization of results using various tools and technologies such as Python, R, SQL, and data visualization tools.
Collaborated with cross-functional teams to implement machine learning models into the company's products and services, increasing accuracy and reducing manual work.

Hindustan Petroleum

October 2022 - March 2023

Database Intern

Collaborated with cross-functional teams to identify and resolve database issues, resulting in a 20% increase in system uptime.
Implemented automated data validation checks, reducing the risk of data inconsistencies by 30%.
Developed and maintained databases to ensure optimal performance and data integrity.
Monitored database performance and made recommendations for improvements.

The Sparks Foundation

September 2022 - October 2022

Data Science and Business Analytics Intern

Conducted exploratory data analysis on a real-world dataset to identify trends and patterns, using Python libraries such as Pandas, Numpy, and Matplotlib.
Developed and evaluated machine learning models for a classification task, achieving an accuracy of 90% using algorithms such as Decision Trees, Random Forests, and Logistic Regression.
Worked with SQL databases to extract and manipulate data for analysis, and used SQL queries to merge multiple datasets from different sources.
Presented findings and insights in a clear and concise manner, using data visualizations and PowerPoint presentations.

BrainyBeam Technologies Pvt. Ltd.

February 2022 - April 2022

Data Science and Machine Learning Intern

Acquired proficiency in Python programming language and popular data science libraries such as Pandas, NumPy, and sci-kit-learn, enabling effective data manipulation, analysis, and modeling.
Collaborated daily with senior members and fellow team members, enhancing communication and teamwork skills in a professional setting.
Designed and implemented a recommendation system that accurately recommends movies to users based on their preferences, utilizing machine learning techniques and algorithms such as collaborative filtering.
Documented day-to-day tasks and learnings in detailed reports, providing valuable insights and knowledge for future reference and analysis.

Research Experience

Cardiovascular Disease Prediction using Genetic Algorithm

January 2023

International Journal of All Research Education and Scientific Methods

Conducted research on cardiovascular diseases, which are a major cause of morbidity and mortality in modern society.
Identified the need for a powerful tool for the accurate prediction of heart disease at a lower cost.
Proposed a system based on common risk factors such as age, family history, diabetes, hypertension, high cholesterol, tobacco smoking, alcohol intake, obesity, and physical inactivity for the early detection of heart disease.
Applied artificial neural network (ANN) and binary classification to the dataset of risk factors for prediction and training of the network.
Developed a model that could potentially help medical professionals diagnose heart disease more accurately and give patients a warning about the probable presence of heart disease before visiting a hospital.

Driver's Drowsiness Detection using Artificial Intelligence

July 2022

International Journal of All Research Education and Scientific Methods

Addressing the serious issue of driver drowsiness and its impact on road safety.
Proposing a hybrid approach that combines vehicle-based and action-based methods for accurate and timely detection of driver drowsiness.
Utilizing advanced neural network techniques and algorithms for the development of the proposed approach.
Highlighting the limitations of current approaches for drowsiness detection and how the proposed approach overcomes them.
Emphasizing the importance of the research for improving road safety and reducing accidents caused by drowsy drivers.