
Data Science with less than a year in ML pipelines and data analysis.
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Entry-level Data Scientist with hands-on experience building end to end ML pipelines. Developed MediSlot Al, a patient no show prediction system achieving 0.7376 AUC-ROC and 89.8% recall on 110,527 healthcare records using XGBoost and SMOTE. Proficient in Python, SQL, and Scikit-learn with a strong foundation in EDA, feature engineering, and model deployment via Streamlit.
MRCE, JNTUH
B.Tech · Computer Science and Engineering
August 1, 2021 – June 30, 2025
Sri Chaitanya Junior College
Intermediate · Class 12
June 1, 2019 – May 31, 2021
SRM High School
SSC · Class 10
June 1, 2018 – May 31, 2019
MediSlot Al - Patient No Show Prediction System
June 1, 2026 – Present
Built an end to end machine learning pipeline to predict patient no shows using 110,527 healthcare records. Engineered features such as WaitingDays, PreviousNoShowRate, and AgeGroup to improve predictive performance. Handled class imbalance (80/20) using SMOTE and optimized models with GridSearchCV. Achieved 0.7376 AUC-ROC and 89.8% recall using tuned XGBoost, prioritizing high-risk patient detection. Deployed an interactive Streamlit application for real-time prediction and decision support.
View ProjectSmart Restaurant Ordering System
June 1, 2026 – Present
Developed a web-based restaurant ordering system supporting dine-in and takeaway services. Designed dynamic menu navigation with real-time bill calculation using JSON data. Implemented session-based cart management for real-time order tracking and updates. Built an automated table allocation system for 15 tables, preventing assignment conflicts. Integrated QR code generation for digital order tracking and payment workflow.
View ProjectFlipkart Mobile Price Exploration (EDA)
June 1, 2026 – Present
Analyzed pricing and specifications of 300+ mobile devices to understand market segmentation. Performed univariate and bivariate analysis on price, RAM, storage, brand, and ratings. Found 10,000-20,000 INR segment had highest average ratings supported by 12 visualizations.
View ProjectGlobal Energy Consumption and Emissions Study
June 1, 2026 – Present
Analyzed data across 40+ countries to evaluate energy consumption and emissions trends. Used joins, aggregations, and window functions for time-series analysis. Identified top 5 countries contributing more than 60% of global CO2 emissions.
View ProjectProgramming with Python
upGrad
June 1, 2026 – Present
SQL and Relational Databases
IBM
June 1, 2026 – Present
Power BI for Data Analysis
Innomatics Research Labs
June 1, 2026 – Present
Exploratory Data Analysis
Innomatics Research Labs
June 1, 2026 – Present
Career Readiness: Young Professional
TCS ION
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects show a diverse interest in data science applications, from healthcare predictions to restaurant systems and market analysis. This breadth suggests adaptability and a willingness to explore different domains. The focus on personal projects indicates self-motivation and initiative, which are positive indicators for cultural fit in a proactive team. The certifications further support a continuous learning mindset.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a structured approach to problem-solving and a focus on practical application. The 'MediSlot AI' project demonstrates an understanding of real-world constraints (class imbalance, prioritizing high-risk patients) and the ability to deliver a functional solution. However, without direct work experience, it's difficult to assess operational fit in a team environment or under pressure.