Help & Supportcareers@gravityer.com
Entry-Level Data Science Professional with Data Analytics and AI Skills
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Highly motivated Computer Science graduate with hands-on experience through academic projects in data interpretation, pattern recognition, and problem-solving. Enthusiastic about applying analytical thinking to extract insights and support decision-making, with a keen interest in emerging AI technologies. Technology enthusiast with a strong aptitude for data analytics.
Annamacharya Institute of Technology and Sciences
Bachelor of Technology · Computer Science and Engineering
August 1, 2021 – June 30, 2025
Tech Layoffs SQL Data Cleaning
January 1, 2025 – December 31, 2025
Designed a safe cleaning pipeline on 2,300+ rows by staging raw data and eliminating duplicates using ROW_NUMBER() Window Functions and CTEs. Resolved data quality issues including NULL/blank inconsistencies, variant category names, trailing characters, and incorrect date types using UPDATE, self-JOIN, TRIM, and STR_TO_DATE. Delivered a fully standardized, analysis-ready dataset by systematically removing irrelevant records and dropping helper columns post-cleaning.
URL Analysis System
November 1, 2024 – March 31, 2025
Analyzed a dataset of 14,000+ URLs to identify patterns distinguishing malicious from benign links across 4 threat categories using Python (Pandas, Scikit-learn) detection. Engineered 22 features from raw URL strings including structural, lexical, and threat-intelligence signals; XGBoost achieved 99.2% overall accuracy, outperforming Random Forest and SVM. Deployed as a real-time Streamlit web app with VirusTotal API integration, enabling end-users to classify URLs as benign, phishing, defacement, or malware on demand.
Introduction to Excel (Microsoft)
Microsoft
June 1, 2026 – Present
Java Full Stack (Wipro)
Wipro
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate initiative and a practical approach to learning, which is a positive indicator for cultural fit in a dynamic data science environment. The diversity of projects (URL analysis, SQL data cleaning) shows a broad interest within the data domain. The stated interest in emerging AI technologies aligns well with an innovative culture. However, the lack of professional experience makes it challenging to fully assess cultural fit in a team setting.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving mindset and attention to detail, particularly in data cleaning and feature engineering. The deployment of a Streamlit app suggests an ability to deliver functional solutions. However, without specific psychometric or English test scores, it's difficult to assess communication clarity, logical reasoning, work attitude, stress handling, or team collaboration beyond what's inferred from project descriptions.