Manas Bichoo
Data ScientistData Maverick
scool.in
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Maverick
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
scool.in
Data Scientist
June 16, 2026 – Present
COVID-Racing-Bar-Chart
June 3, 2020 – June 3, 2020
COVID-Racing-Bar-Chart — GitHub repository
View ProjectStartup-Analysis-EdTech-
May 30, 2020 – May 30, 2020
This is a public repo of a startup analysis research done by me on EdTech sector.
View ProjectYouTube-Subtitle-Analytics
May 22, 2020 – May 23, 2020
YouTube-Subtitle-Analytics — GitHub repository
View ProjectNLP-Web-App-Flask
May 13, 2020 – May 13, 2020
Web Application to demonstrate NLP, made using Flask.
View Projectspellchecker
November 1, 2019 – November 1, 2019
We used NLP(Natural Language Processing) to solve this problem. We used character embedding (chars2vec model) to generate vectorized words and plotted them on vector space to map the closest and semantically similar words together using cosine similarity as the metric. We used a pre trained NLP model called as chars2vec for this purpose. Having the character embedding, every single word’s vector can be formed even it is out-of-vocabulary words. This model is a CNN which performs the character embedding. The step by step solution for this problem statement is: Import the chars2vec model for character embedding. Import the text file and read the words stored in it. Make a array(list) of words of the file. Vectorize all the words of that file by chars2vec model’s vectorize method. Train the chars2vec model with training set as the list of vectorized words. Take an input word from the user. Vectorize the input word using chars2vec vectorize method. Find the cosine similarity of that input
View ProjectSongGenreClassifier
August 19, 2019 – September 12, 2019
SongGenreClassifier — GitHub repository
View ProjectCultural Fit Analysis
The candidate has a range of personal projects, some of which align with the Data Scientist role (e.g., NLP, genre classification, startup analysis). However, the overall project descriptions are brief, and the experience level is listed as 0, despite a current Data Scientist role. This suggests a potential fit for a junior Data Scientist role, but more information is needed to assess cultural fit for a senior position.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights.