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Data Science with less than a year in Machine Learning & MLOps
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 Data Scientist with a strong foundation in analytics, statistics, and Machine Learning. Proficient in Python and SQL, with hands-on experience using libraries such as NumPy, Pandas, and Scikit-learn for building and evaluating ML models and analyzing real-world datasets. Completed MLOps and currently advancing skills in Deep Learning using TensorFlow and Keras.
Vishwakarma Institute of Information Technology
Bachelor of Technology · Information Technology
August 1, 2023 – June 30, 2027
Gopal Krishna Gokhale College
HSC
June 1, 2021 – May 31, 2023
Vimala Goenka English Medium School
SSC
June 1, 2020 – May 31, 2021
Sentiment Analysis with End-to-End MLOps Pipeline
March 1, 2026 – June 1, 2026
Built an end-to-end MLOps pipeline using DVC for data processing, feature engineering, model training, and evaluation Achieved ~89% accuracy by training and comparing Logistic Regression and SVM models with MLflow-based experiment tracking and model versioning Developed a Flask API and deployed using Docker with CI/CD pipeline on GitHub Actions, pushing images to AWS ECR for scalable deployment
Grocery Sales Forecasting for Supermarket Using Machine Learning
January 1, 2026 – June 1, 2026
Built an end-to-end ML pipeline with data cleaning, anomaly detection, feature engineering, and EDA Forecasted supermarket sales using historical and external datasets Implemented and compared Random Forest, Gradient Boosting, and XGBoost models to improve accuracy
Ola Ride Data Analytics Project
July 1, 2025 – June 1, 2026
Simulated and analyzed 1,00,000+ ride records using SQL and Power BI Extracted key metrics including ride distance, cancellations, ratings, and booking value Developed interactive dashboards to visualize ride trends, revenue patterns, and user behavior insights for operational improvements
Machine Learning with Python
IBM (Coursera)
June 1, 2026 – Present
Career Essentials in Data Analysis
Microsoft & LinkedIn
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a proactive approach to learning and applying data science concepts. The diversity of projects (NLP, time series, data analytics) shows a broad interest within the field. However, as an entry-level candidate with no professional experience, the cultural fit is largely unproven and would need to be assessed further during interviews. The current focus is heavily academic.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on structured problems and follow established methodologies (e.g., MLOps pipelines). The academic nature of projects suggests a learning-oriented individual. However, without professional experience or psychometric test results, it's difficult to assess stress handling, team collaboration, or broader operational fit.