Tanmay Sawaji

Data Scientist

https://talent.gravityer.com/tanmay-sawaji

Mumbai, Maharashtra, IndiaMember since June 17, 2026

Key Strengths

Demonstrated interest in data science and machine learning through personal projects like 'Logistic-Regression-with-Regularization' and 'Neural-Network'.
Experience with Python for various applications, including data-related projects and system utilities.
Familiarity with fundamental machine learning algorithms (Logistic Regression, Neural Networks) implemented from scratch.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project portfolio shows a strong inclination towards personal learning and exploration, which can be a positive indicator for a self-starter culture. However, the projects are predominantly individual efforts, making it difficult to assess team collaboration or broader cultural fit. The diversity of projects, from game development to security tools and machine learning, suggests a curious and versatile individual.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

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Projects

dcrypt

November 15, 2024 – December 16, 2024

A simple and secure password manager.

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DCrypt-server

August 6, 2023 – September 16, 2023

A Password Manager server to store all passwords for multiple users.

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StateMachineStack-Pokemon

June 22, 2022 – June 28, 2022

An implementation of the State Machine Stack architecture for playing a basic version of Pokemon

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Coursera_Capstone

August 22, 2020 – August 26, 2020

Capstone Project for the IBM Professional Data Science Course

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Snake-Python

January 10, 2019 – January 10, 2019

This is a snake game created using pygame.

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Electron-Python-Real-Time

November 15, 2018 – November 15, 2018

This is a test communication script between python and electron in real-time.

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Neural-Network

August 31, 2018 – August 31, 2018

This is an implementation of neural network in Matlab/Octave

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Logistic-Regression-One-Vs-All

August 31, 2018 – August 31, 2018

One-vs-All Logistic Regression is used when there are more than 2 output classes

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Logistic-Regression-with-Regularization

August 30, 2018 – August 30, 2018

This repository includes an implementation of Logistic Regression without regularization and one with regularization

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Linux-Keylogger-Python

August 27, 2018 – August 27, 2018

This code runs in the background and stores keystrokes in a log file

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Key Strengths

Demonstrated interest in data science and machine learning through personal projects like 'Logistic-Regression-with-Regularization' and 'Neural-Network'.
Experience with Python for various applications, including data-related projects and system utilities.
Familiarity with fundamental machine learning algorithms (Logistic Regression, Neural Networks) implemented from scratch.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

Tanmay Sawaji

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit