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Kosika Karthik

Technical Support Engineer • Telangana, India • k***************@gmail.com • +91*******548 • linkedin.com/••••• • drivetube.ai/•••••

Career Objective

Technical Support Engineer with 0 years of experience in troubleshooting, ticketing, and technical support; strong foundation in Python and SQL. Proficient in Windows troubleshooting, customer-facing issue resolution, and using ticketing systems (RIVER). Seeking entry-level Technical Support, IT Support, or Service Desk Analyst roles to apply problem-solving and communication strengths while delivering high-quality customer service.

Education

Sri Indu College of Engineering and Technology
B.Tech. Computer Science and Information Technology • Telangana, India • 2025
Narayana Junior College
Intermediate MPC • Telangana, India • 2021
St. Paul’s High School
SSC • Telangana, India • 2019

Technical Skills

Programming Languages: Python
Databases: SQL
Tools and Methodologies: Ticketing systems,RIVER,Remote desktop support
Skills: Python scripting,Object Oriented Programming
Operating Systems: Windows 10,Windows troubleshooting,MS Excel
Networking & Protocols: Networking basics,LAN troubleshooting
Support & Process: Helpdesk support,Incident management,Customer handling,Service desk operations
Analysis & Troubleshooting: Root cause analysis,Problem solving,Data analysis using Excel
Communication & Collaboration: Customer communication,Team collaboration,Time management

Projects

System for Identifying Fake Products Using Blockchain Technology
Tools Used: Python, Data integrity, Distributed ledger concepts
  • Designed a prototype blockchain-based authentication system to record product provenance and reduce counterfeiting risk using Python-based ledger models.
  • Implemented tamper-resistant storage of product data on a simulated distributed ledger to ensure immutable audit trails for verification.
  • Prepared a functional demonstration highlighting how transparent ledger entries enable quicker validation of product authenticity for end-users and vendors.
Optimal Ambulance Positioning for Road Accidents with Deep Embedded Clustering
Tools Used: Python, Clustering, Predictive analysis
  • Developed a predictive framework to identify high-risk locations and recommend ambulance pre-positioning using clustering techniques implemented in Python.
  • Applied embedded clustering to prioritize zones and generate location rankings intended to reduce emergency response times in accident-prone areas.
  • Evaluated model outputs against simulated scenarios to demonstrate potential improvements in coverage and response efficiency.

Certifications

Great Learning Course: Python fundamentals for beginners — Great Learning • 2024
Python Programming — Q-spiders • 2025
English Proficiency (PTE) — Overall score 60/90 — PTE Academic • 2026

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