Rishab Mangal

Data Scientist

https://talent.gravityer.com/rishab-mangal

Software Engineer | Full stack Web Developer | Tech Enthusiast

Infoedge

Key Strengths

Demonstrated interest in Data Science through the 'Smart-Question-Answering-System-on-Document' project, which utilizes deep learning language models for semantic vector conversion.
Experience with Python, a core language for Data Science.
Exposure to Jupyter Notebook, a common tool in data science workflows.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects show a mix of web development (React apps) and a significant data science project. This diversity indicates a willingness to explore different technical areas. The 'Smart-Question-Answering-System-on-Document' project aligns well with the target role of Data Scientist, suggesting a focused interest. However, the overall breadth of skills explicitly listed is limited, and the experience level is 0, indicating a very junior profile for a 'Data Scientist' role.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. Psychometric test scores are 0, providing no insight.

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Projects

muzix

October 13, 2021 – November 15, 2021

muzix screens

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muzix-test

October 5, 2021 – October 5, 2021

muzix test

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Bill_Manager

September 30, 2021 – October 1, 2021

A Simple bill Manager React App

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resume

July 29, 2021 – July 29, 2021

my resume

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sort-Ed

June 3, 2021 – June 3, 2021

React App to visualize different sorting techniques

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mqtt-ChatApp

May 21, 2021 – May 21, 2021

chat app with mqtt and tkinter for GUI

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weather-app

May 10, 2021 – May 11, 2021

A react app to forecast weather

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COiDE

April 30, 2021 – May 5, 2021

Code Editor

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April 28, 2021 – April 28, 2021

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Smart-Question-Answering-System-on-Document

April 26, 2021 – February 3, 2024

It's Smart-Question Answering System on short as well as long documents. It can automatically find answers to matching questions directly from documents. The deep learning language model converts the questions and documents to semantic vectors to find the matching answer.

View Project

Key Strengths

Demonstrated interest in Data Science through the 'Smart-Question-Answering-System-on-Document' project, which utilizes deep learning language models for semantic vector conversion.
Experience with Python, a core language for Data Science.
Exposure to Jupyter Notebook, a common tool in data science workflows.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. Psychometric test scores are 0, providing no insight.

Rishab Mangal

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit