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I’m a passionate innovator with a focus on AI and augmented reality. I aspire to develop cutting-edge technologies that solve real-world problems. I excel in le
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CVR college of engineering
Data Scientist
June 12, 2026 – Present
Celebal_Tech_Assignments
June 2, 2026 – Present
Weekly assignments, codebase implementations, and notes documenting my journey through core mathematics, applied machine learning, and time-series forecasting in the Celebal Tech program.
View ProjectAuto-Read-Me
February 10, 2026 – Present
✨ Stop wasting time on documentation. README Genesis uses AI to synthesize architectural insights into high-conversion READMEs. Visual-first, senior-level docs in < 30 seconds.
View ProjectK-Means_Clustering
January 28, 2026 – Present
Interactive K-Means clustering analysis for wholesale customer segmentation with business insights, stability analysis, and real-time visualizations.
View ProjectStacking_ensemble_model
January 28, 2026 – Present
Stacking Ensemble ML model predicting KC house prices - Streamlit web app
View Projectknn-loan-prediction
January 27, 2026 – Present
An interactive Streamlit dashboard using K-Nearest Neighbors (KNN) to predict and explain credit risk by identifying similar historical customer profiles.
View ProjectRoad_Damage_Detection_DeepLearning
January 22, 2026 – Present
Road_Damage_Detection_DeepLearning — GitHub repository
View ProjectCultural Fit Analysis
The candidate's projects show a strong focus on personal learning and exploration within the data science domain. The diversity of projects, from deep learning for road damage detection to customer segmentation and credit risk prediction, indicates a broad interest in applying machine learning to various problems. The current role as 'Data Scientist' at CVR college of engineering, although with a future start date, aligns directly with the target role. However, the lack of team-based projects or detailed descriptions of collaboration limits the assessment of cultural fit beyond individual initiative.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are brief, and there are no completed psychometric or English tests to provide insight into communication or collaboration styles.