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Data Science with less than a year in AI/ML Engineering & Data Analysis
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AI/ML Engineer and Junior Data Scientist with a strong foundation in Generative AI, machine learning, and data analytics. Proven ability to spearhead NLP sentiment analysis systems, deploy stock prediction models, and build automated data pipelines. Experienced in multi-agent orchestration for candidate-to-job matching and real-time object detection projects. Committed to leveraging data-driven insights and advanced algorithms to solve complex problems and drive innovation.
Periyar University
M.Sc. Data Science · Data Science
N/A – June 30, 2023
Thiruvalluvar University
B.Sc. Computer Science · Computer Science
N/A – June 30, 2021
THEIVANAI AMMAL COLLEGE FOR WOMEN
GUEST LECTURER
June 1, 2024 – May 1, 2025
India
WRIGHT LOGIC
DATA SCIENTIST INTERN
October 1, 2023 – February 1, 2024
Malaysia
ATS RESUME ANALYZER
January 1, 2023 – December 31, 2023
• Pioneered an advanced LangChain/LangGraph RAG pipeline featuring intelligent multi-agent orchestration for automated candidate-to-job matching, achieving 90% matching accuracy across 50+ CVs. • Implemented a high-throughput ingestion pipeline using FAISS vector embeddings, cutting talent screening time by 60% while maintaining matching precision with LLM-powered semantic ranking.
REAL-TIME POTHOLE DETECTION
January 1, 2023 – December 31, 2023
• Deployed a fine-tuned YOLOv8 and OpenCV pipeline achieving 90% detection and localisation accuracy across 1,000+ verification images under varying lighting conditions. • Optimized inference speed to 30+ FPS across 5,000+ road images, enabling real-time production-grade monitoring on edge devices.
ASIAN PAINTS STOCK PRICE FORECASTING
January 1, 2023 – December 31, 2023
• Designed an XGBoost-LSTM hybrid forecasting engine utilizing technical indicators (RSI, Moving Averages) to achieve an R² score of 0.965. • Automated live financial API ingestion pipelines to deliver daily volatility predictions and rolling forecasts, eliminating manual analysis effort entirely.
WIND TURBINE ANOMALY DETECTION
January 1, 2023 – December 31, 2023
• Developed an unsupervised ensemble pipeline combining Isolation Forest and LSTM Autoencoders to detect critical sensory faults occurring in less than 1% of historical operations with high precision and minimal false positives. • Reduced industrial equipment downtime by 25% through proactive multi-sensor predictive analysis and automated real-time alert generation.
ML with Python
IBM
June 1, 2026 – Present
SQL & Databases
IBM
June 1, 2026 – Present
AWS & Azure ML
MS
June 1, 2026 – Present
Data Visualization
Kaggle
June 1, 2026 – Present
Flask Framework
Great Learning
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity (Generative AI, Computer Vision, Time-Series, Anomaly Detection) and experience in both academic and industry settings (internship) suggest adaptability and a broad interest in data science applications. The certifications in AWS & Azure ML indicate a willingness to learn and adapt to cloud-based MLOps practices, which aligns with modern data science team requirements. The focus on practical, problem-solving projects indicates a results-oriented mindset.
Soft Skills & Operational Fit
The candidate's experience as a Guest Lecturer suggests strong communication and mentoring skills, which are valuable for team collaboration and knowledge sharing. Project descriptions indicate a proactive approach to problem-solving and a focus on delivering measurable business impact (e.g., reducing downtime, cutting screening time). The candidate appears to be self-driven and capable of working on diverse projects.