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Data Science with 1+ years in ML model development & deployment
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AI/ML Engineer skilled in ML model development, deployment, and monitoring, with hands-on experience achieving up to 95% accuracy across forecasting, classification, and object detection projects. Strong in Python, ML algorithms, and Flask deployment, with a proven ability to collaborate and deliver production-ready solutions.
Velagapudi Ramakrishna Siddhartha Engineering College – Vijayawada
Master of Computer Applications
N/A – June 30, 2023
Sree Vidya Degree College – Gudivada
Bachelor of Science · Mathematics, Statistics, Computer Science
N/A – June 30, 2021
AudvikLabs Private Limited
Data Science Associate
February 1, 2025 – November 1, 2025
Bengaluru, Karnataka, India
Rubixe - AI Solutions
Data Science Intern
August 1, 2023 – March 1, 2024
India
Tomato Price Forecasting System
June 24, 2026 – Present
Solved the problem of agricultural price volatility by building a time-series forecasting system for tomato prices. Implemented ARIMA for trend and seasonality modeling and Random Forest for feature-based prediction. Performed feature engineering using temperature and historical price data, improving forecast reliability. Achieved 92-95% prediction accuracy with optimized parameters and evaluated performance using RMSE. Applied moving averages to analyze long-term price trends and smooth short-term fluctuations. Collaborated with peers to debug data quality issues and improve model stability.
Product Rating Prediction Web Application
June 24, 2026 – Present
Built an ML-based classification system to predict overall product ratings from structured review data. Processed categorical features (packaging, price, smell) using Label Encoding and data normalization. Trained a Random Forest classifier achieving 94–96% accuracy on validation data. Developed and deployed the model using a Flask web application, enabling CSV file uploads for real-time predictions. Implemented basic model monitoring by tracking input data consistency and prediction distribution after deployment.
Object Detection Using YOLOv5
June 24, 2026 – Present
Designed and trained a custom YOLOv5 object detection model to detect specific regions from video streams. Created and annotated a custom dataset and performed frame extraction from videos for training. Fine-tuned hyperparameters to achieve 90% detection accuracy in real-time scenarios. Integrated the model with OpenCV for live video inference and testing. Supported teammates by resolving annotation errors and improving dataset quality.
Certified Data Scientist(CDS)
Datamites Institute
June 1, 2026 – Present
Certified Data Scientist
NASSCOM (FutureSkills Prime)
June 1, 2026 – Present
Data Science Foundation Certification
IABAC
June 1, 2026 – Present
Problem Solving through Programming in C
NPTEL
June 1, 2026 – Present
Python basic certificate
HackerRank
June 1, 2026 – Present
Data Structure and Algorithms using Java
NPTEL
June 1, 2026 – Present
Data Analytics and Visualization Job Simulation Certificate
Accenture
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity (forecasting, object detection, classification) and experience in both an internship and an associate role suggest adaptability and a broad interest in data science applications. The collaboration mentioned in projects and work experience indicates a team-oriented approach. The certifications further highlight a proactive learning attitude, which aligns well with a growth-oriented culture.
Soft Skills & Operational Fit
The candidate demonstrates collaboration skills through project work and internship experience. The ability to document processes and create reports indicates good operational fit. The project descriptions suggest a problem-solving mindset and attention to detail in achieving high accuracy and handling data quality.