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Assessing your cultural and operational fit
MIT
Data Scientist
June 19, 2026 – Present
docker-nvidia-cuda-cudnn7-ubuntu16.04
February 18, 2019 – February 18, 2019
docker-nvidia-cuda-cudnn7-ubuntu16.04 — GitHub repository
View ProjectTF_Estimator
February 9, 2019 – February 13, 2019
Trying out TF Estimator paired with TF Data pipeline for training and testing. Plots training error, validation error and test error after every epoch.
View Projectlog_analysis_udacity
November 12, 2018 – November 12, 2018
log_analysis_udacity — GitHub repository
View ProjectPlaying_with_Tensorflow
February 18, 2017 – February 19, 2017
This repository will contain Tensorflow code while I learn Tensorflow
View Projectdirected_research
February 6, 2017 – May 8, 2017
This repository will contain code for m y Directed Research on Deep Learning based Lung Cancer Detection
View ProjectCredit_card_fraud_detection
January 10, 2017 – January 10, 2017
Credit_card_fraud_detection — GitHub repository
View ProjectDiabetic_Retinopathy_Detection
January 4, 2017 – January 8, 2017
Code for the kaggle challenge: Diabetic Retinopathy Detection (TensorFlow)
View Projecthand_gesture_recognition
November 13, 2016 – May 22, 2017
hand_gesture_recognition — GitHub repository
View Projectmultiple_output_from_cnn
November 3, 2016 – November 3, 2016
multiple_output_from_cnn — GitHub repository
View ProjectCultural Fit Analysis
The candidate's projects primarily focus on deep learning and machine learning, which aligns with a Data Scientist role. However, the projects are all personal and lack detailed descriptions of collaboration or impact, making it difficult to assess cultural fit beyond technical alignment. The breadth of technologies is somewhat narrow, focusing heavily on Python and TensorFlow.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are brief, and no psychometric or English test scores are available.