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Machine Learning Engineer with less than a year in Data Science & Python
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Detail-oriented MCA graduate with a strong foundation in Machine Learning and Python. Experienced in building predictive models and solving real-world problems using data-driven approaches. Familiar with deep learning concepts, NLP techniques, and model deployment workflows.
Dravidian University, Kuppam
MCA
N/A – Present
Dravidian University, Kuppam
B.Sc. (MSCS)
N/A – Present
Dr. Reddy's Foundation
Data Science Intern
October 1, 2025 – June 1, 2026
India
Speed Detection & Accident Prevention System
January 1, 2026 – Present
ML-based system to detect over-speeding vehicles and alert for accident-prone areas using computer vision. Applied image processing and classification algorithms to analyse vehicle speed from video frames.
Weather Prediction System
January 1, 2026 – Present
Built a predictive model using historical weather data to forecast conditions with Scikit-learn regression. Performed EDA and feature engineering using Pandas and Matplotlib to identify key weather patterns.
Fake News Detection System
January 1, 2026 – Present
NLP-based classifier using TF-IDF vectorisation and Logistic Regression / Naive Bayes to detect fake news. Achieved strong classification accuracy through text preprocessing, feature extraction, and model tuning.
Python Developer
EY
January 1, 2026 – Present
Cybersecurity
edX
January 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity (NLP, Computer Vision, Time Series) and internship experience indicate a willingness to explore different domains within data science and machine learning. The 'AI in Microsoft' achievement suggests engagement with broader AI initiatives. However, the overall experience level is entry-level, which might require significant mentorship to align with senior-level expectations. The target role of Machine Learning Engineer aligns with the candidate's stated skills and project focus.
Soft Skills & Operational Fit
The candidate highlights problem-solving, quick learning, teamwork, and adaptability as strengths. The internship experience suggests exposure to collaborative environments. However, without specific psychometric test results or interview data, the operational fit and depth of these soft skills cannot be fully assessed.