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Data Science with less than a year in Machine Learning & AI
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
As an engineering graduate with a strong foundation in machine learning, I am seeking an opportunity to apply my skills in a competitive environment. I have strong analytical and statistical skills and enjoy working with data to extract meaningful insights that support business decisions.
CMR College of Engineering & Technology
Bachelor of Technology · Artificial Intelligence and Data Science (AI&DS)
January 1, 2021 – January 1, 2025
Narayana Junior College, Hyderabad
Board of Intermediate Education
January 1, 2019 – January 1, 2021
Geetha High School, Medak
Board of Secondary Education
January 1, 2018 – January 1, 2019
Machine Learning-Based Early Childhood Risk Prediction System
June 1, 2025 – Present
Developed a classification model to predict whether a child is risky or healthy. Performed data preprocessing including cleaning and feature engineering. Applied multiple algorithms: Logistic Regression, SVM and Random Forest. Compared model performance to identify the best-performing algorithm. Achieved highest accuracy using Random Forest model. Evaluated models using metrics like accuracy, precision, and recall. Built a system to predict risk category based on input data.
Client-Side Phishing Detection System using Machine Learning
June 1, 2025 – Present
Developed a phishing detection system using Machine Learning techniques. Implemented and trained SVM, Random Forest and XGBoost models. Analyzed features and patterns to classify websites/emails as phishing or legitimate. Applied the system for real-time threat detection to enhance cybersecurity.
EmotionAI: Text-Based Emotion Classification System
June 1, 2025 – Present
Performed data preprocessing and EDA, including removing stopwords, lemmatization, and converting text into numerical format using vectorization techniques. Built a multi-class emotion detection system using NLP to classify text into 8 emotions (like happy, worry, surprise) using models such as Logistic Regression, LSTM, and Bi-directional LSTM. Compared multiple models and selected the best-performing model based on accuracy and performance metrics. Developed and deployed the model to predict emotions from user input text with accurate results.
Artificial Intelligence with Python - Intermediate Level
Infosys Springboard
June 1, 2026 – Present
Certification of Completion – Data Science with Python
Great Learning
June 1, 2026 – Present
Certification of Completion – 1 Month Virtual Internship in Data Science
Coders Cave
June 1, 2026 – Present
Data Analysis using WEKA
Medium Article
June 1, 2026 – Present
SmartPhish Defender: A Machine Learning Approach for Client-Side Web Spoofing Protection
ICCET 2025 (International Conference)
March 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in applying data science to diverse problems (cybersecurity, healthcare, sentiment analysis). This indicates a proactive and curious mindset. The publication of a research paper and certifications show a commitment to continuous learning and engagement with the broader AI/DS community. However, the lack of professional experience or open-source contributions limits the assessment of cultural fit in a corporate setting, particularly regarding adaptability to different team dynamics or business priorities.
Soft Skills & Operational Fit
The candidate lists 'Communication Skills' and 'Team Collaboration' as soft skills. The project descriptions indicate an ability to work through the full lifecycle of a data science project, from data preprocessing to model deployment. However, without direct interview data or team-based project descriptions, it's difficult to fully assess the depth of these soft skills and operational fit in a collaborative, fast-paced environment.