Saahan Bhashetti

Graduate student pursuing a Master's in Data Science with a focus on machine learning and data analytics. Proficient in building scalable machine learning models using Python and scikit-learn, with strong experience in statistical analysis and deep learning.

• Customer Churn Prediction Using Machine LearningObjective: Developed a predictive model to identify customers at risk of churning for an e-commerce platform.
  Approach: Used Python, scikit-learn, and XGBoost to build a classification model using historical customer data. Employed feature engineering techniques and handled imbalanced datasets with SMOTE.
  Results: Achieved an AUC score of 0.89, enabling targeted interventions to retain high-value customers.
  
• Real-Time Media Optimization for Online AdvertisingObjective: Created a model that optimizes online ad placements in real-time to maximize click-through rates (CTR).
  Approach: Used reinforcement learning and deep learning (TensorFlow) for optimization. Built a dashboard to visualize ad performance.
  Results: Improved CTR by 12% through dynamic ad placement.
  
• Product Recommendation System for E-commerceObjective: Designed a collaborative filtering recommendation engine to suggest products based on user behavior.
  Approach: Utilized matrix factorization and k-nearest neighbors (KNN) in Python. Employed collaborative filtering and implemented content-based recommendations.
  Results: Boosted conversion rates by 8% and increased engagement on the website.
  
• Customer Lifetime Value Prediction ModelObjective: Developed a predictive model to estimate customer lifetime value (CLV) using past purchase and behavioral data.
  Approach: Used regression techniques (linear regression, decision trees) with Python and scikit-learn. Integrated RFM (recency, frequency, monetary) analysis to enhance accuracy.
  Results: Provided marketing teams with a forecast accuracy of 85%, improving customer retention strategies.
  
• Sales Operations Analytics DashboardObjective: Built a business intelligence dashboard to analyze sales performance and optimize sales operations.
  Approach: Used R and Tableau for data processing and visualization. Implemented regression models for forecasting sales trends and identifying key performance drivers.
  Results: Helped identify inefficiencies, leading to a 5% increase in quarterly sales productivity.
  

• Participated in Data Hack Hours: Engaged in data-focused hackathon conducted by Anurag University in collaboration with CSI (Computer Society of India) Hyderabad.
• Smart India Hackathon: Participated and secured the 13th position out of 15 teams.
• Anurag University’s Model United Nations (MUN): Acted as a delegate.
• Volunteering Experience: Metaverse AR Workshop
  Google Developer Student Club (GDSC)
• New Role: Appointed as President of the ISTE Student Body for the Department of Artificial Intelligence at your college.

• Deep Learning Specialization – Coursera
• Data Science and Machine Learning Bootcamp – Udemy
• Machine Learning – Coursera (by Andrew Ng)

● Strong interpersonal, written, and verbal communication skills
● Ability to work collaboratively in a team environment
● Excellent problem-solving and critical-thinking abilities
● High attention to detail and accuracy
● Ability to manage multiple tasks and meet tight deadlines
● Demonstrated initiative, good judgment, and resourcefulness

• Recipient of Dean's Merit Scholarship for all the Semesters for Master's