KARTHI S
Python EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Python Engineer with 1+ years in AI/ML & Data Analytics
Python Developer and AI engineer with a B.Tech in Artificial Intelligence and Data Science (CGPA 8.97) and hands-on experience building production-grade computer vision systems, RESTful APIs, and data analytics pipelines. Proficient in Python (OOP, Django, Pandas, NumPy), Oracle SQL, MongoDB, and Power BI. Delivered a real-time YOLO-based object detection system with sub-200ms alert latency and a sales ETL pipeline that cut reporting time by 30%. AWS-certified in Machine Learning and Generative AI. Seeking a Python Developer or Data Analyst role to build scalable, reliable solutions.
Sengunthar Engineering College
B.Tech · Artificial Intelligence and Data Science
August 1, 2022 – June 30, 2026
QSpiders
Data Science Intern
December 1, 2025 – Present
Coimbatore, Tamil Nadu, India
Ruddo
Full Stack Developer Intern
January 1, 2024 – December 31, 2024
India
Blinkit Sales Analytics Dashboard
January 1, 2025 – December 31, 2025
Built an end-to-end sales analytics pipeline processing 8,500+ records in Oracle SQL and Power BI, reducing report generation time by 30% and surfacing 5 actionable KPIs for the business team. Authored 12 optimised Oracle SQL extraction queries and 8 custom DAX measures powering an interactive dashboard with multi-level drill-down, adopted for weekly business reporting.
Wild Animal Detection System
January 1, 2024 – December 31, 2024
Deployed a YOLO-based real-time animal detection system with a Django REST backend, delivering sub-200ms alert generation and logging 1,000+ detection events to MongoDB. Implemented adaptive exception-handling logic for low-light and partial-occlusion conditions, improving detection reliability from ~72% to ~89% accuracy in adverse scenarios. Designed a MongoDB schema with compound indexing optimised for high-frequency writes, reducing log-query retrieval time by ~55% versus an unindexed baseline.
Smart Traffic Management System
January 1, 2024 – December 31, 2024
Engineered a real-time AI traffic monitoring system in Python/OpenCV that automated signal timing across 4 junctions, eliminating manual intervention and reducing average signal-switch latency by ~40%. Architected a 6-module OOP pipeline with full class separation, cutting code duplication by ~60% and enabling independent unit testing of each detection and control layer. Optimised the OpenCV frame-processing pipeline by removing 3 redundant stages, increasing throughput to 30 FPS for stable real-time inference on commodity hardware.
Machine Learning Terminology and Process
AWS Training & Certification
June 1, 2026 – Present
Fundamentals of Generative AI
AWS Training & Certification
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects and internships show a strong interest in AI, data science, and full-stack development, aligning well with innovative and technically challenging environments. Their participation in workshops and paper presentations indicates a proactive learning attitude and engagement with the tech community. The diversity of projects (computer vision, data analytics, e-learning) suggests adaptability and a broad technical curiosity, which can be beneficial in dynamic team settings. However, the experience level is still junior, which might require mentorship in a senior-level team.
Soft Skills & Operational Fit
The candidate demonstrates analytical thinking, problem-solving, and teamwork through project descriptions. Their academic background in AI and Data Science, coupled with practical project experience, suggests a good operational fit for roles requiring data-driven solutions and AI integration. The internships indicate an ability to work in structured environments and contribute to internal tools and platforms.