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Data Science with less than a year in Machine Learning, NLP, and predictive modeling.
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Assessing your cultural and operational fit
Data Science Intern with hands-on experience in Machine Learning, NLP, Recommendation Systems, and predictive modeling. Skilled in Python, SQL, Tableau, and Scikit-learn with experience building and deploying end-to-end ML applications using Streamlit. Completed industry-oriented projects involving data preprocessing, feature engineering, model development, evaluation, and deployment.
Vasireddy Venkatadri Institute of Technology
B.Tech · Information Technology
August 1, 2020 – June 30, 2024
Sri Chaitanya Junior College
Intermediate
June 1, 2018 – May 31, 2020
Andhra High School
Secondary School Certificate
June 1, 2017 – May 31, 2018
ExcelR – Aivariant
Data Science Intern
June 1, 2025 – March 1, 2026
India
Product Recommendation System
June 1, 2026 – Present
Developed a personalized recommendation system to suggest relevant products based on user preferences and interaction patterns. Business Need & Solution: Businesses require personalized recommendations to improve customer engagement and sales. Implemented recommendation techniques using data preprocessing, feature analysis, and similarity-based approaches to generate accurate product suggestions. Outcome: Delivered anNinteractive recommendation application that improves user experience by providing personalized product recommendations.
Resume Classification System
June 1, 2026 – Present
Developed an automated resume classification system to categorize candidate profiles into suitable job domains. Business Need & Solution: Recruiters spend significant time manually screening resumes. Applied NLP techniques, text preprocessing, feature extraction, and machine learning models to automate resume categorization. Outcome: Created an efficient screening solution that reduces manual effort and improves the recruitment process.
Alzheimer's Disease Classification
June 1, 2026 – Present
Developed a machine learning system to predict Alzheimer's disease risk using patient data. Business Need & Solution: Early identification of Alzheimer's risk helps healthcare professionals make informed decisions. Applied data preprocessing, feature selection, classification algorithms, and model optimization techniques for accurate prediction. Outcome: Built an interactive prediction system enabling faster and data-driven healthcare assessment.
Masters Program in Data Science
NASSCOM
June 1, 2026 – Present
Data Science Program Completion
ExcelR Solutions
June 1, 2026 – Present
Google Data Analytics
Coursera
June 1, 2026 – Present
Azure AI Fundamentals
Microsoft
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects cover diverse domains (recruitment, e-commerce, healthcare), indicating adaptability and a broad interest in applying data science. The listed certifications (NASSCOM, ExcelR, Coursera, Microsoft Azure) show a commitment to continuous learning and professional development. The target role of 'Data Science' aligns well with the candidate's stated skills and project experience. The candidate's experience level is entry-level, which is consistent with the internship and personal projects.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an understanding of business needs and the ability to translate them into technical solutions. Participation in a hackathon suggests a proactive and problem-solving attitude. The internship experience, though future-dated, outlines practical application of data science skills in a professional setting. However, without direct assessment of communication or teamwork, these aspects are inferred from project descriptions.