Vidhi Bafna

Mathematically grounded Artificial Intelligence student specializing in discrete optimization, AI planning, and intelligent decision-making systems. Experienced in modeling real-world problems using MiniZinc, supervised learning, and data analytics. Proven communication and teaching skills developed through extensive tutoring in mathematics and physics. Committed to contributing to collaborative research environments while enhancing expertise in optimization and AI reasoning.

• Complete Python Developer, Udemy, 2022
• Multi-variable Calculus, Swayam, 2019
• Data Science course, Intellipat, 2022-2023
• Complete Machine Learning 2023 Course, Udemy, 2024

• Implemented data validation processes, resulting in a data accuracy rate of 98%.
• Identified key trends and patterns in customer behavior, leading to a 15% increase in sales conversion rate.
• Developed interactive dashboards using MetaBase, improving data accessibility and decision-making.
• Worked with and assessed the digital marketing team of the company to help enhance the company's reach, generate leads, creating content and poster.
• Maintaining current knowledge of relevant technologies and optimized work with Artificial Intelligence tools.

Customer Retention Model, Developed a Participant Retention Model to identify high-risk participants and support the business' retention strategy., Implemented the model, resulting in the retention of 650 participants and a worth of $139M Assets AUM., Utilized Logistic Regression and Random Forest algorithms. Automatic Machine Learning Algorithm Deployment Model, Built an autonomous machine learning workflow for deploying models with minimal user effort., Created a workflow that runs autonomously on CSV files and returns the best performing model. NLP-based Chatbot for Industrial Safety, Developed an NLP-based chatbot for industrial safety, aiming to understand and mitigate workplace accidents., Analyzed accident records from 12 different plants across 3 countries., Designed an ML/DL-based chatbot utility to highlight safety risks based on incident descriptions. Telephone Company Customer Behavior Prediction, Analyzed historical customer data to predict behavior and improve customer retention strategies for a telecom company., Identified patterns and pinpoints of customer churn, enabling the company to focus on effective retention programs.