
ML Engineer | Data Scientist | Developer | Pentester. Computer Science graduate from NIT Andhra Pradesh.
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI_EVM
January 14, 2021 – November 28, 2021
An Electronic Voting Machine Powered by AI. ATM like voting system. Phases included are Persons detection, Face mask detection, Face recognition, Voting on screen. Django as backend
View ProjectFirebase-Phone-Auth-Demo
March 29, 2020 – June 16, 2021
Demo Project to show how to use Phone Authentication in Flutter with Firebase backend
View ProjectGraphical-Password-User-Authentincation
November 12, 2019 – October 6, 2023
A Django project demonstrating Graphical Password Authentication system. It uses combination of images as password. Functions include password reset, Block account on failed attempts, Notification when failed attempt occurs.
View ProjectMyNIT-App
April 20, 2019 – January 13, 2021
Flutter Mobile App for College students called MyNIT App. Developed using Firebase & Flutter.
View ProjectGoogle-Chrome-Password-Grab
March 25, 2019 – March 24, 2020
This is a test project to demonstrate how vulnerable google chrome passwords are, that can be accessed by anyone who can open your browser right away
View ProjectHacker-Script
September 3, 2018 – January 17, 2021
Automated bash script for tasks such as detecting devices & their mac ids around, faking mac id & NMAP scan with options.
View ProjectCultural Fit Analysis
The candidate's personal projects show a diverse range of interests, from mobile app development to cybersecurity and AI. While this indicates a broad curiosity, the direct alignment with a dedicated 'Data Scientist' role is moderate. The 'Lead-Scoring-Case-Study' and 'AI_EVM' projects are most relevant, suggesting an interest in data-driven solutions. However, the overall project portfolio lacks depth in advanced statistical modeling, machine learning algorithms, or big data technologies typically expected for a senior Data Scientist. The absence of professional experience or education details makes it difficult to fully assess cultural fit within a structured team environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.