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ML Engineer with less than a year in Python, Machine Learning & NLP
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Science enthusiast with hands-on experience in Python, Machine Learning, NLP, and model deployment using FastAPI and Streamlit. Completed a 9-month internship building ML pipelines and deploying predictive models. Skilled in data cleaning, EDA, and building end-to-end ML solutions.
Aditya Degree College
Bachelor of Computer Applications (BCA)
August 1, 2020 – June 30, 2024
Aditya Junior College
Intermediate
June 1, 2018 – May 31, 2020
Bhashyam Public School
SSC
June 1, 2017 – May 31, 2018
AI Variant
Machine Learning Intern
September 1, 2025 – Present
India
Fake News Detection using NLP
June 1, 2026 – Present
Built NLP model using TF-IDF and Logistic Regression. Achieved 99% accuracy and deployed using Streamlit. Performed text preprocessing and EDA.
Stock Market Analysis & Prediction
June 1, 2026 – Present
Analyzed historical stock data and built Decision Tree model. Created visual dashboards and reduced RMSE using feature engineering. Deployed prediction app using Streamlit.
Machine Learning Model Deployment API
June 1, 2026 – Present
Trained ML model and deployed as REST API using FastAPI. Tested endpoints using Postman for real-time predictions.
Data Science
ExcelR, Hyderabad
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in Machine Learning and NLP, aligning well with an ML Engineer role. The diversity of projects (stock prediction, fake news detection, API deployment) shows a breadth of application. The internship experience further solidifies this alignment. However, the overall experience level is entry-level, which might require significant mentorship and integration into a senior team's culture. The candidate's self-identified strengths in communication and collaboration are positive for cultural fit, but without further evidence, it's hard to fully assess.
Soft Skills & Operational Fit
The candidate lists 'Problem Solving', 'Communication', 'Team Collaboration', and 'Quick Learner' as strengths. Project descriptions also mention 'Problem Solving', 'Communication', and 'Team Collaboration'. While these are positive indicators, there is no external assessment data (e.g., psychometric test results) to objectively validate these claims. The candidate's experience is primarily academic and internship-based, suggesting a foundational understanding of operational workflows but lacking extensive real-world operational experience.