Andaaz Moun

About Andaaz Moun

As a Computer Science and Engineering student specializing in Artificial Intelligence and Machine Learning at Chandigarh University, I’m passionate about building AI-driven solutions to address real-world challenges. My journey in technology fuels my drive to develop scalable machine learning models, data-driven systems, and cloud-native applications. At Celebal Technologies, I developed ChurnAdvisor, a churn prediction model using XGBoost and SHAP, enhancing customer retention for a telecom client. Through additional hands-on experiences, I’ve led advanced AI projects, applying cutting-edge ML techniques to deliver industry-relevant solutions. These efforts, combined with mini-projects in Python, Pandas, and SQL, including my GitHub-hosted AI-powered regulatory compliance checker, have honed my expertise in data engineering, predictive analytics, and Generative AI. What makes me unique is my ability to blend technical precision with business impact, transforming complex data into actionable insights. Proficient in Machine Learning, RAG, AI and cloud technologies, I thrive in fast-paced environments. I’m excited to join innovative teams in tech, finance, or healthcare to drive AI-powered progress. Let’s connect to build transformative solutions together!

Experience

1. Data Science Intern

   Celebal Technologies

   Jun 2025 — Present

   Developed and deployed ChurnAdvisor, an end-to-end machine learning application, integrating XGBRFClassifier and Cox Proportional Hazards models to predict customer churn and timing, achieving 85% prediction accuracy and enabling data-driven retention strategies.Engineered a context-aware insight engine using SHAP to deliver actionable, customer-specific recommendations, enhancing decision-making for business stakeholders.Designed and launched an interactive Streamlit dashboard for real-time and batch churn predictions, featuring SHAP beeswarm plots, which improved user engagement by 30% during testing.Mastered Python libraries (NumPy, Pandas, Scikit-learn, Seaborn, XGBoost) and SQL to perform data wrangling, exploratory data analysis (EDA), and feature engineering, reducing data preprocessing time by 25%.Applied machine learning techniques (Regression, Classification, Clustering) across weekly mini-projects, improving model performance by up to 15% through iterative experimentation.Built and tested a Generative AI RAG chatbot using document-based data, streamlining information retrieval and boosting query response accuracy by 20%.Collaborated with cross-functional teams to complete assignments, strengthening core data science concepts and delivering 100% of project milestones on time.

Education

• DAV Schools Network

  12th

• CHANDIGARH UNIVERSITY

  Bachelor of Engineering - BE

  2022