Subir

Data Scientist

https://www.opentalent.in/subir-1

Applied Scientist 2@Amazon

Amazon

Key Strengths

Demonstrated experience with various Machine Learning and Deep Learning projects, including NLP and anomaly detection.
Proficiency in Python and Jupyter Notebook, essential tools for Data Scientists.
Experience with FastAPI and Dockerfile for deploying ML models, indicating MLOps awareness.
Current role as Data Scientist at Amazon suggests relevant industry experience, though no start date is provided.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily personal and demonstrate a strong interest in various data science domains. The current role at Amazon aligns well with a Data Scientist position. However, the lack of diverse team projects or contributions beyond personal repositories makes it difficult to fully assess cultural fit. The experience level is listed as 0, which contradicts the current role at Amazon, indicating a data discrepancy.

Soft Skills & Operational Fit

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

AI is analyzing your overall score…

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Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

semantic-search-with-sbert

June 4, 2021 – April 26, 2022

Build Semantic Search with S-BERT and Fine-tune your model in unsupervised way

View Project

fastapi-template

December 29, 2020 – May 28, 2025

Completely Scalable FastAPI based template for Machine Learning, Deep Learning and any other software project which wants to use Fast API as an API framework.

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NLP-house

December 8, 2020 – May 28, 2025

NLP-house — GitHub repository

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Sentiment-Analysis-Web-App

October 17, 2020 – December 29, 2020

Sentiment Analysis Flask-Restplus based Web app. The backed model is BERT powering the classification Engine.

View Project

Predictive-Customer-Analytics

October 3, 2020 – October 3, 2020

Understanding the customer life cycle Acquiring customer data Applying big data concepts to your customer relationships Finding high propensity prospects Upselling by identifying related products and interests Generating customer loyalty by discovering response patterns Predicting customer lifetime value (CLV) Identifying dissatisfied customers Uncovering attrition patterns Applying predictive analytics in multiple use cases Designing data processing pipelines Implementing continuous improvement

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Anomaly-Detection

April 30, 2020 – December 8, 2022

Different Components of Anomaly Detection

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Miscellaneous

February 7, 2020 – May 28, 2025

Miscellaneous — GitHub repository

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DeepLearning

May 3, 2018 – May 28, 2025

Deep Learning / NLP Projects and Experiments

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Machine-Learning

March 27, 2016 – May 28, 2025

Implementation of various ML algorithms on different data sets

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Audio-Watermarking

March 12, 2016 – April 26, 2020

This is MATLAB code for blind audio watermarking using Arnold transform and ECC

View Project

Key Strengths

Demonstrated experience with various Machine Learning and Deep Learning projects, including NLP and anomaly detection.
Proficiency in Python and Jupyter Notebook, essential tools for Data Scientists.
Experience with FastAPI and Dockerfile for deploying ML models, indicating MLOps awareness.
Current role as Data Scientist at Amazon suggests relevant industry experience, though no start date is provided.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

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

Subir

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit