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Assessing your cultural and operational fit
helper-scripts
February 28, 2025 – March 14, 2025
A whole bunch of web attack payloads with names that suggest they're helpful
View ProjectBinaryQuantileRegression
September 18, 2021 – September 25, 2021
Codebase for the paper Estimation and Applications of Quantiles in Deep Binary Classification
View ProjectNoise2Noise-audio_denoising_without_clean_training_data
March 28, 2021 – September 1, 2023
Source code for the paper titled "Speech Denoising without Clean Training Data: a Noise2Noise Approach". Paper accepted at the INTERSPEECH 2021 conference. This paper tackles the problem of the heavy dependence of clean speech data required by deep learning based audio denoising methods by showing that it is possible to train deep speech denoising networks using only noisy speech samples.
View ProjectQA_VoiceBot_Desktop_Application
July 30, 2019 – October 23, 2021
end-to-end voicebot that answers open domain questions.
View ProjectThirtyDaysofGo
February 24, 2019 – March 15, 2019
My solutions for Hackerrank's 30 Days of Code challenge using Go
View Projectbadcalc
January 30, 2019 – January 30, 2019
Multifunction Calculator with graphing and function storage
View Projectjournal_classifier_mer
January 30, 2019 – January 30, 2019
Classifies Journals as national or international using a Minimum Error Rate Classifier
View ProjectCreditCard_NeuralNetwork
March 21, 2018 – March 22, 2018
Experimenting with Keras and Tensorflow using a dataset found kaggle on credit card fraud
View ProjectCobraChess
November 29, 2017 – November 29, 2017
This is a simple 2 Player chess game on command line, made using Python3. Adapted from & inspired by https://github.com/liudmil-mitev/Simple-Python-Chess
View ProjectCultural Fit Analysis
The candidate's projects show a strong focus on machine learning and data science, which aligns with a Data Scientist role. The diversity of projects, from audio denoising to credit card fraud detection and journal classification, indicates a broad interest within the ML domain. However, the lack of team-based projects or contributions to open-source initiatives makes it difficult to fully assess cultural fit beyond technical alignment. The 'helper-scripts' project, while technically oriented, lacks a clear description of its purpose or impact, making it hard to evaluate its relevance to a professional setting.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are concise, but there is no information on collaboration, problem-solving approaches, or communication style in a team setting.