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AI Engineer with less than a year in Python, Machine Learning & Data Analysis.
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/ML Engineer with a strong foundation in Python, Machine Learning, and data analysis. Experienced in developing predictive models and analyzing transactional data using key libraries like Scikit-Learn, TensorFlow, and Pandas. Proven ability in data visualization, data cleaning, and feature engineering, with academic projects demonstrating practical application in financial data and house price prediction.
AAA COLLEGE OF ENGINEERING AND TECHNOLOGY
B.E · Computer Science and Engineering
August 1, 2020 – June 30, 2024
KALAIMAGAL HIGHER SECONDARY SCHOOL
12th PERCENTAGE
June 1, 2018 – May 31, 2020
KALAIMAGAL HIGHER SECONDARY SCHOOL
10th PERCENTAGE
June 1, 2016 – May 31, 2018
House Price Prediction Model
July 1, 2024 – December 1, 2024
Built and trained regression models to predict house prices based on features such as area, location, and rooms. Achieved 90% accuracy using Random Forest and Linear Regression.
Paytm Transaction Data Analysis
January 1, 2024 – June 1, 2024
Collected and analyzed Paytm transaction data to identify user spending patterns. Created data visualizations using Power BI and Matplotlib for better insights.
Machine Learning with Python
GUVI
June 1, 2026 – Present
SQL for Data Science
GUVI
June 1, 2026 – Present
Power BI Fundamentals
GUVI
June 1, 2026 – Present
Certificated Python Developer
Eduprep
June 1, 2026 – Present
Certificated MySQL Developer
Eduprep
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic background and project work indicate an interest in data-driven problem-solving, which aligns well with an AI Engineer role. The diversity of tools and concepts explored (data analysis, visualization, predictive modeling) suggests a broad interest within the AI/ML domain. However, the lack of professional experience or diverse project types beyond academic settings limits the assessment of cultural adaptability and collaboration in a professional environment.
Soft Skills & Operational Fit
The candidate's academic projects demonstrate problem-solving skills and an ability to apply theoretical knowledge to practical scenarios. The certifications suggest a self-driven approach to learning and skill development. However, without professional experience or psychometric test results, it is difficult to assess stress handling, team collaboration, or broader operational fit.