Mohd Uzaif
Data ScientistLearning ~ Developing ~ Evolving
JMI
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Learning ~ Developing ~ Evolving
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
JMI
Software Engineer
June 15, 2026 – Present
fastapi-patient-records-api
June 6, 2026 – Present
Learning FastAPI and Pydantic through practical projects, REST API development, data validation, request handling, and backend best practices.
View Projectxgboost-intuition-and-implementation
April 17, 2026 – Present
An in-depth implementation of XGBoost covering gradient boosting theory, regularization, and optimized tree learning. Includes experiments on real-world datasets with detailed comparisons against baseline models and performance metrics analysis.
View Projectgradient-boosting-intuition-and-implementation-
April 7, 2026 – Present
Deep dive into Gradient Boosting with intuitive explanations, mathematical foundations, and hands-on implementation in Python.
View Projectrandom-forest-intuition-and-implementation
April 1, 2026 – Present
A comprehensive guide to Random Forest covering intuition, working principles, and implementation from scratch, along with practical examples for classification and regression.
View Projectdecision-tree-intuition-and-implementation
March 29, 2026 – Present
Implementation of Decision Tree using CART algorithm with detailed insights into Gini impurity, split selection, feature importance, and pruning techniques.
View ProjectSVM-from-scratch-and-scikit-learn
March 19, 2026 – Present
A complete implementation of Support Vector Machine (SVM) from scratch along with practical applications using Scikit-learn. Covers hard margin, soft margin, kernel trick, and visualization for better understanding.
View Projectlogistic-regression-from-scratch-to-sklearn
March 18, 2026 – Present
A complete implementation of Logistic Regression from scratch to scikit-learn, including binary and multiclass (One-vs-Rest) classification with evaluation and visualization.
View Projectnaive-bayes-from-scratch
March 7, 2026 – Present
Implementation and intuitive explanation of the Naive Bayes Classifier for machine learning, including probability concepts, mathematical intuition, and a practical Python example.
View Projectmodel-evaluation-and-selection
March 1, 2026 – Present
A practical repository covering model evaluation metrics, ROC-AUC analysis, threshold tuning, cross-validation, and model selection techniques using Scikit-learn.
View ProjectCamera_App
March 21, 2023 – March 21, 2023
Structured this project using HTML, CSS and JavaScript.
View ProjectCultural Fit Analysis
The candidate demonstrates a strong self-learning initiative through numerous personal projects focused on fundamental machine learning algorithms. However, the projects are predominantly academic implementations rather than real-world applications or collaborative efforts. The single listed work experience as 'Software Engineer' at JMI is current with no start date, making it difficult to assess professional experience or team collaboration. The lack of diverse project types (e.g., deployment, MLOps, data engineering) and the absence of explicit team-based projects limit the assessment of cultural fit for a senior Data Scientist role.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a proactive learning approach and a focus on understanding fundamental concepts.