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Aman Adhav

Computer Science Student | Software Engineer | Data Scientist

📞 +1 (623) 276-6989 ✉️ avadhav@asu.edu 💼 LinkedIn 📍 Tempe, AZ

Computer Science undergraduate at Arizona State University with hands-on experience in full-stack development, distributed systems, and data analytics. Proficient in multiple programming languages and frameworks with a strong understanding of software architecture, cloud deployment, and machine learning. Passionate about building high-performance, scalable solutions that leverage AI and data-driven insights to solve real-world problems. Seeking opportunities to contribute to innovative projects while continuing to grow as a software engineer and data scientist.

Technical Skills

Programming Languages & Libraries

Python3 Java C++ JavaScript HTML CSS PyTorch NumPy Pandas Scikit-learn XGBoost Linux

Frameworks & Technologies

Backend

Django Flask Spring Boot Node.js (Express) FastAPI

Frontend

React.js JavaScript HTML5 CSS3

Databases & Cloud Services

AWS (EC2, S3, RDS, Lambda) MySQL PostgreSQL MongoDB Redis Docker CloudWatch

Data Science & Analytics

Machine Learning Statistical Analysis Predictive Modeling Data Visualization Tableau Power BI A/B Testing ETL

Core Concepts

Data Structures & Algorithms Object-Oriented Programming Software Architecture DevOps CI/CD Microservices RESTful APIs Unit Testing

Work Experience

Software Engineering Intern

📅 May 2024 - August 2024 | 40 hours/week

Rachita Infotech

Built a full-stack web application using React.js, Node.js, and Express with RESTful APIs and MongoDB, improving project tracking efficiency by 40%
Deployed containerized microservices via Docker and AWS (EC2, S3, RDS) with GitHub Actions CI/CD pipeline
Implemented comprehensive unit and integration tests using Jest and Supertest, achieving 90%+ code coverage
Optimized application performance with Datadog & AWS CloudWatch monitoring, reducing latency by 25%

Data Science Intern

📅 May 2023 - August 2023 | 40 hours/week

Rachita Infotech

Predicted customer churn with 86% accuracy using Scikit-learn, XGBoost, and StatsModels
Cleaned and transformed 10M+ row datasets with Pandas and SQL, reducing processing time by 30%
Conducted A/B tests and statistical analyses (t-tests, ANOVA) to measure product impact
Built interactive Tableau and Power BI dashboards to visualize customer behavior and KPIs
Deployed ML models via Flask API in Docker on AWS Lambda and monitored with CloudWatch

Teaching Assistant

📅 July 2024 - Present | 20 hours/week

Arizona State University

Led sessions and provided one-on-one tutoring to support freshmen in mastering algebra and calculus
Graded assignments and exams for nearly 100 students, ensuring timely and constructive feedback

Projects

CineMind – LLM-Enhanced Movie Recommendation System

May 2025 - August 2025

Developed a movie recommendation platform integrating Collaborative Filtering, Matrix Factorization, and Item-based KNN on the MovieLens 20M dataset
Built an LLM-powered conversational chatbot enabling users to request recommendations via natural language (moods, genres, vague prompts)
Designed scalable backend services in Python (Scikit-learn, Pandas, Surprise), deployed with JavaScript/HTML/CSS frontend
Achieved 12% lower RMSE than baseline models through advanced algorithm optimization

Python Scikit-learn Pandas LLM AWS

ClassQ – Intelligent Course Scheduling & Queueing System

May 2025 - August 2025

Engineered a Redis-based queueing system simulating 1,000+ concurrent registrations under 200ms latency
Built conflict-free scheduling logic considering credit limits, time conflicts, and professor ratings
Developed with FastAPI backend and React.js frontend, deployed on AWS infrastructure

Redis FastAPI React.js AWS

Customer Churn Analytics & Prediction

May 2025 - August 2025

Developed a churn prediction pipeline on a large-scale customer dataset
Applied feature engineering and trained XGBoost and Logistic Regression models, achieving an AUC of 0.91
Created interactive Tableau dashboards for churn risk segmentation
Recommended targeted retention strategies based on predictive insights

XGBoost Python Tableau SQL

Certifications

Supervised Machine Learning: Regression and Classification

Stanford University

Creating Engaging Chatbots with ChatGPT & Large Language Models

Online Certification

Get In Touch

📧 Email

avadhav@asu.edu

📱 Phone

+1 (623) 276-6989

💼 LinkedIn

linkedin.com/in/aman-adhav

📍 Location

Tempe, Arizona, USA