Data Science with less than a year in Machine Learning & Analytics, skilled in Python, SQL, and Powe
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Analytical and results-driven Data Scientist with expertise in Machine Learning, Statistical Modeling, and Advanced Analytics. Experienced in building scalable predictive models, performing end-to-end data analysis, and delivering actionable business insights. Skilled in Python, SQL, Power BI, Tableau, and predictive analytics with hands-on experience in dashboard creation, model optimization, and data storytelling.
JPNCE College of Engineering
Bachelor of Technology · Computer Science Engineering
August 1, 2021 – June 30, 2025
Prathibha Junior College
Intermediate
June 1, 2019 – May 31, 2021
Heera Model School
Secondary School Certificate
June 1, 2019 – May 31, 2019
Cognifyz Technologies
Data Analysis Intern
December 1, 2025 – January 31, 2026
India
Internship Studio
Machine Learning Intern
April 1, 2025 – May 31, 2025
India
Flight Fare Prediction System
June 1, 2026 – Present
Designed an end-to-end ML pipeline for airfare prediction using 10,000+ records. Applied advanced preprocessing and feature engineering techniques. Built and compared multiple models including Random Forest, XGBoost, and ANN. Reduced RMSE by 70% compared to baseline regression models.
Credit Card Fraud Detection
June 1, 2026 – Present
Processed 50,000+ transaction records to detect fraudulent activities. Resolved class imbalance using SMOTE and resampling techniques. Improved Recall score by 18% and achieved ROC-AUC score of 0.94.
COVID-19 Data Analysis & Forecasting
June 1, 2026 – Present
Conducted time-series forecasting and infection growth analysis. Built regression models to predict trend patterns. Created visual reports for comparative state-wise insights.
Sales Analytics Dashboard
June 1, 2026 – Present
Performed SQL-based transformations and KPI analysis. Built interactive Power BI dashboards for revenue tracking. Identified business growth opportunities using trend analysis.
Home Loan Default Prediction
June 1, 2026 – Present
Performed EDA, feature engineering, missing-value treatment, and class-imbalance handling. Built a machine learning model to predict loan default risk using customer, bureau, and repayment data. Optimized models with a focus on Recall to reduce financial risk and improve identification of potential defaulters. Generated actionable insights for risk assessment and lending decisions.
NBA Shot Selection Prediction
June 1, 2026 – Present
Analyzed Kobe Bryant's shot selection data and developed predictive models to determine scoring probability. Performed EDA and feature engineering using shot distance, location, game context, and shot type. Compared Logistic Regression, Random Forest, XGBoost, Neural Networks, and other models using Accuracy and F1-Score. Built a shot prediction framework to support coaching decisions and game strategy optimization.
Generative AI 101
GUVI & HCL
June 1, 2026 – Present
Python Programming
Cisco Academy
June 1, 2026 – Present
Cybersecurity Fundamentals
Cisco Academy
June 1, 2026 – Present
AI Tools Workshop
Be10X
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects cover a diverse range of data science applications, from finance (fraud detection, loan default) to sports analytics (NBA shot prediction) and public health (COVID-19 analysis). This breadth demonstrates adaptability and a willingness to apply skills across different domains. The internships, though short, show initiative in gaining practical experience. The certifications in Python and Generative AI indicate a proactive approach to learning and staying current with industry trends, which aligns well with a culture of continuous improvement.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an analytical and results-driven approach. The focus on reducing RMSE, improving Recall, and achieving specific ROC-AUC scores suggests a detail-oriented mindset. The ability to build dashboards and generate actionable insights points to good communication and presentation skills for operational fit.