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Sachin Kolase | Gravity Talent Portal

Sachin Kolase

Sachin Kolase

Data Scientist

https://talent.gravityer.com/sachin-kolase

Working as Associate Research Manager in Kantar

Kantar Millward Brown

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Mumbai, Maharashtra, IndiaMember since June 16, 2026

https://talent.gravityer.com/sachin-kolase

Top Skills

RPythonJupyter NotebookCSSHTML

Skills

RPythonJupyter NotebookCSSHTML

Experience

Kantar Millward Brown

Data Scientist

June 16, 2026 – Present

Projects

MAchine-Learning-Transformation-Techniques

May 6, 2021 – May 6, 2021

MAchine-Learning-Transformation-Techniques — GitHub repository

Flight-Price-Prediction-HEROKU

April 25, 2021 – April 25, 2021

Flight-Price-Prediction-HEROKU — GitHub repository

Flight-Price-Prediction_End-to-End-_Heroku

April 25, 2021 – April 25, 2021

Flight-Price-Prediction_End-to-End-_Heroku — GitHub repository

FlaskApp_Zomato_Rating_Prediction

April 25, 2021 – April 25, 2021

FlaskApp_Zomato_Rating_Prediction — GitHub repository

StreamlitApp_EDA-Visualization-Model

April 25, 2021 – April 25, 2021

StreamlitApp_EDA-Visualization-Model — GitHub repository

Streamlit-App

April 25, 2021 – April 25, 2021

Streamlit-App — GitHub repository

Twitter-data-download-using-GOT3

May 16, 2019 – May 16, 2019

This code downloads the tweets from Twitter and perform analysis on them. The library used here is GotOldTweets3 which has no restriction on days limit

Simple-Chatbot-using-NLTK-in-Python

September 30, 2018 – September 30, 2018

This post consist of code as well as description of various steps required to build simple chatbot using NLTK library from pyhton. Along with text pre processing I have used cosine similarity to match the words from corpus and question asked by user.

Text-Analysis-

August 21, 2018 – August 21, 2018

Text analysis of PM Modi speech by using quanteda package in r

Algorithmic-Trading

July 3, 2018 – July 27, 2018

Algorithmic-Trading — GitHub repository

Key Strengths

Demonstrated interest in Data Science through multiple personal projects.
Experience with Python for data analysis, machine learning, and web application development (Flask, Streamlit).
Exposure to Natural Language Processing (NLTK) and text analysis.
Practical application of machine learning for prediction tasks (Flight Price, Zomato Rating).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project portfolio shows a strong inclination towards practical application of data science concepts, which aligns with a results-oriented culture. The diversity of projects (NLP, algorithmic trading, price prediction, web apps) indicates a willingness to explore different domains within data science. However, the lack of team-based projects or detailed descriptions of collaboration limits a deeper assessment of cultural fit.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights.