
Data Analyst with less than a year in Data Analysis & Machine Learning.
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Saurav Ray is an aspiring Data Analyst, Data Scientist, and Machine Learning enthusiast with 6 months of internship experience. He has a strong foundation in data cleaning, preprocessing, and exploratory data analysis, demonstrated through projects involving AI-driven news summarization, interactive healthcare dashboards, and student dropout prediction using machine learning. With a proficiency in Python, SQL, R, and various data visualization tools, Saurav is passionate about leveraging data to generate actionable insights and drive data-driven decision-making.
Lovely Professional University
Bachelor of Technology · Computer Science Engineering
August 1, 2022 – June 30, 2026
Main Flow Services
Data Analyst Intern
February 1, 2025 – July 1, 2025
Jalandhar, Punjab, India
Student Dropout Prediction using Machine Learning
June 1, 2026 – Present
Built an end-to-end machine learning system to predict student dropout risk using academic, attendance, financial, and demographic indicators. Evaluated and benchmarked 6 machine learning models, including XGBoost, Random Forest, and Logistic Regression, using Precision, Recall, F1-score, and ROC-AUC metrics to identify the best-performing model. Built and deployed an interactive Streamlit dashboard with SHAP-based explainability to classify students into Low, Medium, and High-risk categories and recommend personalized retention interventions.
View ProjectHealthcare Analytics Dashboard
May 1, 2026 – Present
Designed and deployed an interactive healthcare analytics dashboard visualizing 9,216+ ER patient records from 2019–2020 to monitor patient flow, wait times, and referral trends. Processed healthcare datasets using Python (Pandas) and developed Power BI dashboards to track 7+ operational KPIs, including average wait time (35.26 min), patient satisfaction, and department referrals. Recreated and deployed the dashboard on Netlify using HTML, JavaScript, and Chart.js, enabling responsive web-based reporting and interactive filtering across 2 years of patient data.
View ProjectExamMemory AI — AI-Powered News Aggregation & Recommendation System
April 1, 2026 – Present
Designed and deployed an AI-driven news summarization system that processed 1,000+ news articles monthly, generating exam-focused summaries and MCQs for UPSC/SSC aspirants. Engineered a Python-based automation pipeline for RSS news ingestion and filtering, reducing manual content curation effort by approximately 70%. Implemented quiz systems, spaced repetition, leaderboards, and automated PDF exports to improve user engagement and revision efficiency.
View ProjectCloud Computing
NPTEL
May 1, 2025 – Present
R Programming
Board Infinity
September 1, 2024 – Present
SQL For Data Science
Great Learning
June 1, 2024 – Present
Cultural Fit Analysis
The candidate's diverse personal projects (news aggregation, healthcare analytics, student dropout prediction) showcase initiative and a broad interest in applying data analysis and machine learning to different domains. This diversity, coupled with an internship, indicates a strong drive for practical application and continuous learning, aligning well with a dynamic, project-oriented team culture. The range of technologies used (Python, R, SQL, various ML libraries, dashboarding tools) suggests a willingness to explore and adopt new tools.
Soft Skills & Operational Fit
The candidate demonstrates a proactive approach to learning and project execution, as evidenced by multiple personal projects and certifications. Their ability to work with diverse datasets and technologies suggests adaptability. The psychometric test score indicates average performance in areas like logical reasoning and work attitude, which might require further assessment in an interview.