Machine Learning Engineer with less than a year in Python and 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
Motivated Computer Science Engineering (Data Science) undergraduate with practical experience in Machine Learning, data preprocessing, and data analysis using Python. Skilled in Pandas, NumPy, Scikit-learn, Flask, and SQL with strong problem-solving abilities.
Raghu Engineering College, Visakhapatnam
B.Tech · Computer Science Engineering (Data Science)
August 1, 2022 – June 30, 2026
Narayana Junior College
Intermediate · MPC
June 1, 2020 – May 31, 2022
Priya Ushodaya School
SSC
N/A – May 31, 2020
IPL Win Probability Predictor
June 1, 2026 – Present
Developed a real-time IPL win probability prediction system using Machine Learning and historical IPL match datasets from Kaggle. Engineered match-based features such as Current Run Rate (CRR), Required Run Rate (RRR), wickets remaining, balls remaining, and target score to improve prediction accuracy. Trained and evaluated a Logistic Regression model using Scikit-learn for second-innings outcome prediction. Built a Flask-based REST API with endpoints like /predict, /teams, and /cities for dynamic frontend integration. Implemented JSON validation, exception handling, and CORS support for reliable API communication. Serialized the end-to-end ML pipeline using Pickle to enable fast inference without retraining the model. Organized the project with modular backend architecture and deployment-ready configuration files including requirements.txt and runtime.txt. Managed source code and version control using Git and GitHub.
View ProjectMachine Learning
Unknown
June 1, 2026 – Present
Python Programming
Unknown
June 1, 2026 – Present
SQL
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate is an undergraduate with a focus on Data Science, aligning well with a Machine Learning Engineer role. The personal project demonstrates initiative and a practical application of learned skills. The breadth of skills listed (Python, Java, SQL, various ML libraries, DSA, OOPs) indicates a foundational interest in diverse technical areas. However, the lack of professional experience or diverse project types limits a comprehensive assessment of cultural fit beyond technical alignment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on structured problems and implement end-to-end solutions. The modular architecture and deployment-ready configurations suggest an understanding of good software engineering practices. However, without direct experience or psychometric test results, it's difficult to assess stress handling, team collaboration, or broader operational fit.