Data Science with less than a year in Python, Machine Learning & Data Analytics
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Soham Kadam is an aspiring Data Science professional with strong skills in Python, Machine Learning, and Data Analytics. With a background in Mathematics and Computing, Soham has led impactful academic projects like an AI-Powered Hybrid Intrusion Detection System and a Smart Healthcare Analytics System. Experienced in developing and deploying intelligent solutions, Soham is eager to contribute to innovative teams in the field.
Rajiv Gandhi Institute of Petroleum Technology (RGIPT)
B.Tech. · Mathematics and Computing
August 1, 2023 – June 30, 2027
Lal Bahadur Shastri Senior Secondary School
Senior Secondary
N/A – May 31, 2022
Oxford International School
Secondary
N/A – May 31, 2020
AI-Powered Hybrid Intrusion Detection and Prevention System
January 1, 2026 – June 1, 2026
Built a hybrid cybersecurity system integrating 3 ML and DL models trained on the CICIDS2017 dataset, achieving real-time NORMAL/ATTACK network traffic classification. Developed a Flask REST API to ingest live Suricata logs with sub-second prediction latency; generated confusion matrix and feature importance visualizations to evaluate model performance across 15+ attack categories.
View ProjectSmart Healthcare Analytics System
January 1, 2026 – June 1, 2026
Developed and deployed a healthcare analytics dashboard that predicts 6 disease classes across 20,000+ patient records with 99% accuracy; features disease distribution analysis, blood pressure insights, and feature importance visualizations.
View ProjectAI Fitness Calorie Tracker
January 1, 2026 – June 1, 2026
Deployed a calorie-burn prediction web application achieving R-squared score of 0.99 using 7 physiological input features; includes a BMI calculator, workout intensity insights, and feature importance visualization identifying exercise duration and heart rate as the top 2 predictors.
View ProjectCA-MBE-QLMR: Congestion-Aware Multipath Routing in SDN
January 1, 2025 – June 1, 2025
Designed a Max-Boltzmann Q-Learning routing algorithm for SDNs with congestion-aware action masking; modeled as an MDP achieving 40% faster convergence and staying within 10 to 15% of ILP-optimal across 5 load factors and 5 random seeds. Added ILP verification for optimality gap analysis, blockchain-hashed audit trails, and ablation studies (No-CA and No-MBE) with fully automated and reproducible experiment scripts.
View ProjectCultural Fit Analysis
The candidate's projects are diverse, covering areas like cybersecurity, healthcare, fitness, and network routing, indicating a broad interest in applying data science to various domains. This diversity suggests adaptability and a willingness to explore different problem spaces. The academic focus of all projects, while demonstrating strong technical skills, means there is no direct evidence of cultural fit within a corporate environment, such as experience in agile methodologies, cross-functional team collaboration, or navigating corporate structures. The target role 'Data Science' aligns well with the candidate's project portfolio and technical skills.
Soft Skills & Operational Fit
The candidate demonstrates initiative and leadership through their 'Co-Head, Security Team' role. Project descriptions indicate an ability to work on complex problems and deliver functional applications. The academic nature of all projects suggests a strong theoretical foundation but limited exposure to industry-standard operational practices, team collaboration in a professional setting, or handling production-level challenges. The candidate's experience level is 0, which aligns with their current academic status.