Analytically driven professional with a background in data analysis, adept at optimizing productivity and task efficiency. Specialize in AI, machine learning, predictive modeling, and big data analytics. Bring critical thinking, problem-solving, and teamwork skills to excel in collaborative environments.
Hi, I’m
Mathiyazhagan Ganeshan
Chennai,TN
Summary
Overview
3
years of professional experience
1
Certification
Work History
Amazon Development CenterChennai
Quality Services
01.2021 - 01.2024
Job overview
- Cross-Platform Testing: - Conducted cross-platform testing for Fire Tablets, ensuring consistent functionality across different OS versions, screen sizes, and hardware configurations.
- Tested integration with other Amazon services (e.g., Alexa, Prime Video, Kindle) to ensure seamless functionality within the Fire Tablet ecosystem. - Performance & Load Testing: Conducted performance testing to evaluate the responsiveness and stability of the Fire Tablet software under various load conditions. Analyzed performance metrics, and collaborated with development teams to identify and resolve bottlenecks.
- Continuous Improvement: - Actively participated in retrospectives, providing feedback and suggestions for process improvements that resulted in higher test coverage, and quicker turnaround times.
- Bug Reporting and Root Cause Analysis: Led the identification and documentation of critical defects, worked closely with developers to conduct root cause analysis, and proposed solutions to prevent future occurrences.
- Played a key role in defect triage sessions, ensuring that high-priority bugs were addressed promptly to meet release deadlines. - Collaboration and Knowledge Sharing: - Mentored and supported junior testers in learning automation tools and techniques, fostering a collaborative environment for skill growth. - Worked closely with developers and QA engineers to implement best testing practices, ensuring consistency in testing procedures across the team.
- Exploratory Testing: - Performed exploratory testing to uncover edge cases and issues that were not covered by the existing test scripts, providing additional coverage and product quality insights.
- Reported edge cases and suggested improvements, enhancing the overall robustness of the product.
Education
Dr. MGR Educational And Research Institute
BACHELOR OF TECHNOLOGY from ELECTRONICS AND COMMUNICATION ENGINEERING
01.2019
University Overview
- Project: Smart Universally Remote Accessibility-Based Home Automation System
- The proposed system enables the use of IOT to make the existing system range less for controlling home appliances. IOT module and embedded C programming are implemented to construct the system. It modifies existing software to correct errors, upgrade interfaces and improve performance.
- GPA: 67 %
- Member of the (KALAM 2018 community)
ALPHA MATRICULATION HIGHER SECONDARY SCHOOLCHENNAI
HSC from COMPUTER SCIENCE
04-2015
University Overview
Skills
- Interpersonal Skills
- Analytical Skills
- Critical Thinking
- Detail-Oriented
- Adaptability
- Team Player
- Software Testing
- Jira
- Appium
- PyCharm
- MS Office
- Java
- Python
- Machine learning
- PyTorch framework
- Image processing
- Natural language processing(NLP)
- TensorFlow framework
- Agile methodology
- Artificial intelligence research
- Fuzzy logic systems
- Keras library
- Neural networks
- Algorithm development
Languages
Tamil
First Language
English
Proficient (C2)
C2
Hindi
Proficient (C2)
C2
Timeline
Quality Services
Amazon Development Center
01.2021 - 01.2024
Dr. MGR Educational And Research Institute
BACHELOR OF TECHNOLOGY from ELECTRONICS AND COMMUNICATION ENGINEERING
ALPHA MATRICULATION HIGHER SECONDARY SCHOOL
HSC from COMPUTER SCIENCE
Personal Information
Personal Information
Date of Birth: 15/05/1997
Personal projects
Personal projects
AI-Powered Chatbot for Customer Service
Developed and implemented an AI-driven chatbot to automate and enhance customer support experiences. The chatbot utilized Natural Language Processing (NLP) to understand and respond to customer queries, improving response accuracy and efficiency. Integrated Machine Learning algorithms to learn from past interactions, enabling the bot to provide personalized responses and resolve common issues without human intervention. Deployed across web and mobile platforms, the system handled over 70% of customer inquiries autonomously, reducing human agent workload and improving response time by 40%.
Technologies Used: Python, spaCy, TensorFlow, RNN, NLP, cloud deployment (AWS/GCP), Dialogflow.
Outcome: Increased customer satisfaction by 30%, decreased operational costs, and ensured 24/7 support availability, allowing human agents to focus on complex queries.
Personal Information
Personal Information
Date of Birth: 15/05/1997
References
References
References available upon request.Similar Profiles
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