SIDDAREDDYGARI MYTHILI

Python / SQL – CrateDB Intern

https://talent.gravityer.com/siddareddygari-mythili

Key Strengths

Strong foundational knowledge in AI/ML concepts, including Neural Networks, Deep Learning, NLP, CNN, and LSTM, demonstrated through certifications and academic projects.
Proficiency in Python and relevant AI/ML frameworks/libraries such as TensorFlow, OpenCV, and Cryptography Library.
Practical experience applying ML/AI techniques to solve real-world problems through academic projects like Recommendation Systems, Image Encryption, and Fraud Detection.
Proactive in self-learning and skill development, evidenced by multiple Coursera and AWS certifications in data analysis, big data, and deep learning.
Academic background in Computer Science with a specialization in Data Analytics, directly aligning with the target AI/ML Software Engineer role.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

About

Highly motivated Computer Science and Engineering student specializing in Data Analytics with strong skills in Python, Java, SQL, Power BI, and Machine Learning. Experienced in developing innovative projects including Credit Card Fraud Detection, Smart Career Advisor using Machine Learning, and Secure Image Encryption systems. Possess hands-on internship experience, strong analytical abilities, and a passion for solving real-world problems through technology. Eager to contribute technical expertise, teamwork, and problem-solving skills in a challenging engineering role.

Education

Alliance University. Bangalore

Bachelor of Technology (B.Tech) · Computer Science and Engineering (Data Analytics)

September 4, 2022 – May 30, 2026

Projects

Credit Card Fraud Detection

September 1, 2025 – Present

Developed a Machine Learning-based Credit Card Fraud Detection system to identify fraudulent financial transactions with high accuracy. Performed data preprocessing, feature scaling, handling of missing values, and imbalance treatment using techniques such as SMOTE. Implemented and compared multiple machine learning algorithms including Logistic Regression, Decision Tree, Random Forest, SVM, and XGBoost to improve fraud prediction performance. Evaluated models using precision, recall, F1-score, ROC-AUC, and confusion matrix analysis. The project focused on minimizing false positives while ensuring efficient real-time fraud detection for secure financial transactions.

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Image Encryption for Secure Image Transfer

January 4, 2024 – November 29, 2024

Developed a secure image encryption system for protecting confidential image data during transmission over insecure networks. Implemented image compression, encryption, and decryption functionalities using Python and cryptographic techniques including Fernet, AES, and RSA algorithms. Integrated secure image transfer through Email (SMTP) and WhatsApp using Twilio API. Worked on image processing, key generation, secure communication, and performance optimization to ensure data confidentiality and efficient transmission. Collaborated in system design, testing, and implementation of the project modules.

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Certifications

Oracle Analytics Cloud 2025 Certified Professional

Oracle University

June 2, 2025 – December 30, 2027

Solutions Architecture Job Simulation

Forage

April 30, 2025 – Present

Data Analytics Internship

Intrainz

August 1, 2024 – Present

Key Strengths

Strong foundational knowledge in AI/ML concepts, including Neural Networks, Deep Learning, NLP, CNN, and LSTM, demonstrated through certifications and academic projects.
Proficiency in Python and relevant AI/ML frameworks/libraries such as TensorFlow, OpenCV, and Cryptography Library.
Practical experience applying ML/AI techniques to solve real-world problems through academic projects like Recommendation Systems, Image Encryption, and Fraud Detection.
Proactive in self-learning and skill development, evidenced by multiple Coursera and AWS certifications in data analysis, big data, and deep learning.
Academic background in Computer Science with a specialization in Data Analytics, directly aligning with the target AI/ML Software Engineer role.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate exhibits a strong cultural fit for an AI/ML Software Engineer role, primarily due to their focused academic specialization in Data Analytics, highly relevant academic projects, and proactive pursuit of certifications in AI/ML and big data technologies. This demonstrates a clear passion for the field, a commitment to continuous learning, and an ability to apply theoretical knowledge, which are valuable traits in a dynamic tech environment.

Soft Skills & Operational Fit

The candidate's participation in a 'Placement Training Bootcamp' suggests an awareness and effort towards developing aptitude, coding, and soft skills. However, without direct evidence from completed assessments or detailed project descriptions, a comprehensive evaluation of soft skills, problem-solving approaches, and collaboration capabilities is not possible. The psychometric test score is 0, providing no data.