Ayush Raney

Aspiring data analyst with practical experience in Python, SQL, and Power BI. I have built and deployed complete analytical and machine learning projects, including time-series forecasting, classification models, and interactive dashboards for real-world datasets. My leadership roles managing large events and coordinating across teams have helped me communicate insights clearly to both technical and non-technical people.

• Certificate of MERIT, SUMMER ANALYTICS'25 - CAC IIT Guwahati

Summer Internship | National Informatics Centre May 2025 - June 2025

• Conducted A/B testing analysis to evaluate CPDS platform design alternatives and optimize user data interaction.
• Employed SQL queries and Power BI dashboards to visualize chemical data trends for stakeholder reports.
• Automated data processing workflows with Python scripts to enhance accuracy and efficiency in real-time data handling.

Stock Market Prediction and forecasting using deep learning 

• Engineered time-series inputs and applied MinMax scaling with strict chronological train/validation/test splits to prevent leakage.
• Trained and tuned a stacked LSTM and validated model stability with holdout evaluation and predicted vs. actual visualizations.
• Packaged an end-to-end forecasting pipeline to support data-driven trend analysis and decision making .

Emotional Classification Speech Processing 

• Developed CNN-BILSTM-Attention model on Log-Mel Spectrograms for 8-emotion classification ( 82% accuracy, 83% macro-F1).
• Implemented end-to-end preprocessing: audio normalization, pseudo-augmentation, and dynamic class balancing.
• Deployed model via Streamlit app for real-time emotion prediction from user-uploadaudio .

Credit Card Behavior Score Prediction Using Classification and Risk-Based Techniques  

• Built ML pipeline for default prediction using data cleaning, feature engineering, and SMOTETomek for imbalance.
• Trained & tuned Random Forest, LightGBM, XGBoost to optimize F2-score ( 80% accuracy, 0.70 recall, 0.54 F2).
• Derived actionable insights for repayment behavior, credit utilization, and risk-based customer segmentation.

Bank Loan Report Analysis

• Created dashboards (Power BI, Excel) to track loan KPIs and month-on-month growth.
• Ensured 100% data integrity via SQL validation; risk segmentation revealed a 13.8% bad-loan rate.
• Performed Python (pandas) trend analysis by state, month, and loan purpose to generate strategic insights.

Senior Executive Member (Editorial) | Academic Council  

• Led academic events like the Placement Preparation Series, collaborating with alumni and industry experts to deliver career-development sessions. Streamlined policy communication between administration and students, managing rollout of revised UG&PG curriculum.

Executive Member (Operations) | Sports Council 

• Oversaw operational planning and on-ground execution for major sports events Colours Trophy, Sangram24, and Inter-Bhawan Sports Championship. Managed logistics, scheduling, participant registration, and volunteer teams to ensure seamless, safe event delivery.