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AI Research Engineer with less than a year in Machine Learning & 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
Aspiring AI/Machine Learning Engineer with a B.Tech in Information Technology and hands-on experience in Machine Learning, Data Analytics, and AI-driven projects. Proficient in Python, SQL, Scikit-learn, NumPy, and Pandas. Familiar with NLP, Generative AI, LLMs, RAG concepts, and data preprocessing. Strong analytical and problem-solving skills with experience in developing predictive models, data analysis, and business intelligence solutions.
Dhanalakshmi Srinivasan Engineering College
Bachelor of Technology · Information Technology
January 1, 2021 – December 31, 2025
AI-Powered Earthquake Early Warning System
June 1, 2026 – Present
Developed a deep learning-based earthquake prediction model using Python and MySQL. Performed data preprocessing, model training, and evaluation for real-time prediction.
House Price Prediction System
June 1, 2026 – Present
Built a regression model using Scikit-learn for property price prediction. Deployed the application using Streamlit for real-time predictions.
Web Scraping & Data Analysis
June 1, 2026 – Present
Extracted and analyzed product data using Python, BeautifulSoup, and Pandas. Generated actionable insights through data analysis and visualization.
Sales Analysis & Car Sales Dashboard
June 1, 2026 – Present
Analyzed customer and revenue trends using SQL. Developed an interactive Power BI dashboard using DAX and data visualization techniques.
Machine Learning with Python
IBM
June 1, 2026 – Present
Data Analysis with Python
IBM
June 1, 2026 – Present
Python 101 for Data Science
IBM
June 1, 2026 – Present
SQL Mastery
I.T. Vedant
June 1, 2026 – Present
Python Essentials
I.T. Vedant
June 1, 2026 – Present
Power BI Fundamentals
I.T. Vedant
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects are primarily academic and focus on individual contributions, which is typical for an entry-level profile. The diversity of projects (prediction systems, data analysis, web scraping, dashboards) shows a broad interest in data-related fields. The target role of 'AI Research Engineer' aligns with the candidate's stated interests and project work, particularly the deep learning and predictive modeling aspects. However, the lack of professional experience and team-based projects limits the assessment of cultural fit in a collaborative research environment.
Soft Skills & Operational Fit
The candidate lists problem-solving, analytical thinking, team collaboration, communication, time management, and quick learning as soft skills. These are generally positive attributes for an AI Research Engineer role, indicating a potential for growth and adaptability within a team environment. However, without direct assessment data, the actual operational fit regarding these skills remains unverified.