Help & Supportcareers@gravityer.com
AI Engineer with 1+ years in Python, Pandas & Scikit-learn.
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 and results-driven Data Science and Machine Learning Intern with 1.2 years of practical experience in data analysis, model development, and Python programming. Skilled in leveraging libraries like Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn for tasks such as data cleaning, feature engineering, and predictive modeling. Proven ability to build and evaluate machine learning models for applications like crop production and air quality prediction, demonstrating a strong foundation in data-driven problem-solving.
Vignan's Institute of Information Technology
Bachelor of Technology · Information Technology
August 1, 2022 – June 30, 2026
Unicoverage Technologies Pvt Ltd
DataScience & MachineLearning Intern
July 1, 2025 – Present
India
Edunet Foundation
ArtificialIntelligence & Data Analytics Intern
November 1, 2024 – December 31, 2024
India
Center for Training and Employment
Python Development Intern
May 1, 2024 – June 30, 2024
India
Agriculture Production Prediction
July 1, 2025 – Present
• Developed a machine learning model to forecast agricultural crop production in India using historical data (2001-2014) from data.gov.in. • Conducted data cleaning, preprocessing, and exploratory data analysis (EDA) to handle missing values, identify production trends, and understand cost-yield relationships. • Applied regression-based models (Linear Regression, Random Forest, XGBoost) and evaluated performance using metrics such as R2 score and RMSE.
Air Quality Index Prediction
November 1, 2024 – December 31, 2024
• Predict future AQI levels using historical pollutant and weather data to support timely pollution control measures. • Identify key environmental factors (e.g., PM2.5, PM10) affecting air quality for better policy planning. • Developed a machine learning model (Random Forest) achieving 92% accuracy, enabling reliable AQI forecasting for real-time monitoring.
Cultural Fit Analysis
The candidate shows a strong interest in AI and data analytics, aligning well with an AI Engineer role. The diversity of projects (agriculture, air quality, e-commerce) indicates adaptability and a willingness to explore different domains. The continuous engagement in internships suggests a driven individual eager to gain practical experience, which is a positive cultural fit for a growth-oriented environment. However, the experience is primarily academic and internship-based, indicating a need for mentorship and structured development within a professional team.
Soft Skills & Operational Fit
The candidate's resume indicates a proactive approach to learning and applying data science skills through multiple internships and academic projects. The descriptions are clear, suggesting good communication of technical work. The focus on practical application aligns with operational needs for an AI Engineer role, though the experience level is junior.