Data Science with 1+ years in Python, ML, and Data Analytics.
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 Data Science & Machine Learning Intern with 1.0 years of hands-on experience in data cleaning, preprocessing, feature engineering, and model development. Proficient in Python (Pandas, NumPy, Scikit-learn) and visualization tools (Matplotlib, Seaborn). Proven ability to build and evaluate machine learning models for predictive analytics, achieving high accuracy in real-world projects like crop production and air quality forecasting.
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 – June 30, 2026
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's projects and internships show a clear focus on data science and machine learning, aligning well with the target role. The diversity in project domains (agriculture, air quality) indicates adaptability and a willingness to apply skills to different challenges. The Python development internship, while not directly data science, shows a broader technical interest and foundational software development skills, which can be beneficial. However, the experience level is entry-level, and the projects are academic, which might require more mentorship in a professional setting.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on structured problems and follow established data science workflows. The academic projects and internships suggest a foundational understanding of problem-solving within a data science context. However, there is insufficient data to assess advanced soft skills like leadership, complex stakeholder management, or independent problem framing.