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Data Scientist @CIODS
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CIODS
Data Scientist
June 21, 2026 – Present
Kidney-Disease-Classification
September 29, 2024 – October 1, 2024
Kidney-Disease-Classification — GitHub repository
View ProjectEmail-spam-classifier
September 21, 2024 – September 21, 2024
This GitHub project is an Email Classifier that distinguishes between spam and ham using Naive Bayes. It is built with Python, trained on labeled data, and deployed via Flask for web interaction. The project is hosted on Render for seamless live deployment and easy accessibility.
View Projectmnisar.github.io
September 16, 2024 – October 4, 2024
Showcases my portfolio, featuring various data science and machine learning projects. Each project includes detailed descriptions, code, and visualizations. It's designed for easy navigation and demonstrates my expertise in Python, SQL, and Flask, with deployment on platforms like Render and GitHub Pages.
View ProjectDiabetes-Analysis-Tableau
September 14, 2024 – September 14, 2024
Diabetes Analysis and Suggestions: A Tableau project providing an in-depth analysis of diabetes data. Explore trends, risk factors, and patient outcomes through interactive dashboards. Utilize advanced visualizations to uncover insights, patterns, and actionable recommendations for improving diabetes management and research.
View ProjectCovid19-Data-Insights.sql
September 14, 2024 – September 14, 2024
Covid19-Data-Analysis: SQL scripts for exploring and analyzing Covid-19 data. Includes queries for infection rates, death percentages, population impact, and vaccination coverage. Utilizes joins, CTEs, temp tables, and views for comprehensive insights. Ideal for data scientists focusing on Covid-19 trends.
View Projectaustralia-rain-prediction
September 14, 2024 – September 14, 2024
Developed logistic regression, random forest, and decision tree models to predict rainfall in Australia using weather data like temperature, humidity, and wind speed. This project covers data preprocessing, feature selection, model training, and evaluation. The models aim to classify whether it will rain tomorrow, improving weather forecasts.
View Projectinsurance-premium-prediction
September 14, 2024 – September 14, 2024
This project demonstrates building a basic machine learning model to predict annual medical expenses using customer data (age, BMI, smoking habits, etc.) for ACME Insurance Inc. The model helps estimate monthly premiums, with a focus on transparency and explainability, making it beginner-friendly and easy to understand.
View ProjectFace-Recognition
June 9, 2023 – August 7, 2023
The project includes code for face recognition, implemented for use in smart glasses designed for the visually impaired. Using OpenCV, the system accurately detects and identifies faces, providing real-time assistance to the blind by recognizing and notifying them of people around them.
View ProjectCultural Fit Analysis
The candidate has a diverse set of personal projects covering various data science applications (e.g., medical analysis, weather prediction, spam classification, face recognition). This breadth suggests curiosity and a willingness to explore different problem domains, which can be a positive indicator for cultural fit in a dynamic environment. However, the experience level is listed as 0, and the only listed professional experience is current with a future start date, making it difficult to assess real-world collaboration and team fit. The target role is 'Data Scientist', and the projects align well with this role, demonstrating relevant technical interests.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to articulate technical work. The variety of personal projects suggests initiative and a proactive approach to learning and applying data science concepts. However, without psychometric test results, a comprehensive assessment of soft skills and operational fit is not possible.