
AI Engineer with 1+ years in Data Science & Machine Learning
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A highly skilled and analytical professional pursuing M.Tech in Computer Science and Engineering with AI and ML. Possesses 1.0 years of hands-on experience as a Data Scientist and Data Analyst, specializing in developing AI/ML models, automating data processes, and creating interactive dashboards. Proficient in Python, data science tools, and cloud platforms like AWS, with a strong background in natural language processing, computer vision, and machine learning for impactful data-driven solutions.
Sarvajanik College of Engineering & Technology
BTech · Computer Engineering with Specialization in Data Science
N/A – June 1, 2025
Vellore Institute of Technology
MTech · Computer Science and Engineering with AI and ML
N/A – June 1, 2026
Network 18
Data Scientist Intern
June 1, 2025 – August 1, 2025
India
Maruti InfoSoft
Data Analyst Intern
January 1, 2025 – April 1, 2025
India
IBM SkillsBulid
Data Analytics Intern
June 1, 2024 – August 1, 2024
India
Mentorness
Data Analyst Intern
May 1, 2024 – June 1, 2024
India
Online News Popularity
June 18, 2026 – Present
Developed a Scikit-learn model to predict social media virality and optimize content strategy.
SQLGenie
June 18, 2026 – Present
Chatbot - Converted natural language prompts to SQL queries using OpenAI API and Streamlit.
Classification of Multiple Eye Diseases using Pre-trained Convolution Neural Network
IEEE
February 1, 2025 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, including personal projects, internships across different companies (Network 18, Maruti InfoSoft, IBM SkillsBuild), and academic leadership roles, indicates adaptability and a proactive learning attitude. The focus on AI/ML and data science aligns well with an AI Engineer role, suggesting a strong interest and commitment to the field. The breadth of skills and tools used demonstrates a willingness to explore and adopt new technologies.
Soft Skills & Operational Fit
The candidate's resume highlights experience in team collaboration (GDSC Data Science Lead, IEEE WIE Membership Development Chair) and problem-solving. The project descriptions indicate an ability to work on end-to-end solutions and automate processes, which aligns with operational efficiency. The academic leadership roles suggest initiative and mentorship capabilities.