Badr Jaidi, Developer in Vancouver, Canada
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Badr Jaidi

Verified Expert  in Engineering

Artificial Intelligence Developer

Vancouver, Canada
Toptal Member Since
May 5, 2022

Badr is a data scientist specializing in natural language processing. He speaks four languages fluently and has been in the technology field for nearly a decade, where he has worked on a broad range of projects going from hardware to front-end development.


Plutoshift, Inc.
Data Science, Python, Machine Learning, Time Series, Signal Processing
Bhavik Muni
Generative Pre-trained Transformers (GPT), GPT...
Ai Outcome
Python, Topic Modeling, Text Classification, SpaCy, Gensim, Machine Learning...




Preferred Environment

Visual Studio Code (VS Code), Unix

The most amazing...

...product I've developed is a topic modelling pipeline that handles bilingual text and brings insights to clients on hundred of thousands of documents.

Work Experience

Data Scientist

2022 - 2022
Plutoshift, Inc.
  • Trained high accuracy time series classification models for a Fortune 500 company.
  • Preprocessed huge amounts of complex time series hardware signals into an interpretable and trainable format.
  • Used various complex time series transformations and machine learning techniques to do time series classification.
Technologies: Data Science, Python, Machine Learning, Time Series, Signal Processing

NLP Expert

2022 - 2022
Bhavik Muni
  • Implemented an NLP solution that extracts actionable insights from YouTube-related text data.
  • Efficiently extracted large amounts of text data from YouTube's platform.
  • Designed an architecture that combines the NLP analytics and then extracted data to display insights live to the client.
Technologies: Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT), Data Science, GPU Computing

Data Scientist

2019 - 2021
Ai Outcome
  • Researched and developed a topic extraction model that led to the creation and sales of a new product.
  • Developed an optimized and efficient bilingual French and English text processing pipeline.
  • Used time series forecasting to help clients manage their resources more efficiently.
  • Set up and managed a database server infrastructure to host hundreds of gigabytes of raw data.
Technologies: Python, Topic Modeling, Text Classification, SpaCy, Gensim, Machine Learning, Data Science, Artificial Intelligence (AI), Deep Learning, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), GPT, Full-stack

Teacher Assistant

2018 - 2021
École de Technologie Supérieure
  • Assisted researchers by conducting experiments in a THz research lab.
  • Helped students learn to program in C by assisting them through the whole learning cycle, from the basics to making their first project.
  • Helped students learn to use Linux platforms, install, manage, configure their networks, and use a bash script to automate them.
Technologies: Waveforms, C, Unix, Cisco, Bash Script, MATLAB

Software Developer

2018 - 2019
iBwave Solutions
  • Developed features for an application used by hundreds of clients worldwide.
  • Tracked and resolved bugs using Jira as a reporting tool.
  • Contributed to quality insurance by testing the application thoroughly.
Technologies: C#, Agile, QA Testing

Associate Developer

2016 - 2017
  • Developed parts of web and iOS applications and set up databases for a diverse range of customers.
  • Created a map application that smoothly displayed live data from millions of database rows.
  • Maintained the company's internal chatbot regularly.
Technologies: SQL, C#, Swift, JavaScript, Java, PHP, HTML, Bootstrap, Full-stack

Fake News Classification
The project's goal was to train a model capable of detecting fake news.

Two models were trained and compared. A linear model with FastText and a neural model with TensorFlow. With the training data, the neural model gave the best results, but on manually annotated data from online news, FastText performed much better.

This showed that linear models are very good at generalizing, and neural models need to be trained on lots of good data to perform well.

Legal Corpus NER
The project's goal was to build an annotated corpus from scratch with a browser interface for non-experts.

The data was scrapped from BC's Court of Appeal and Supreme Court and was annotated using label-studio.

BERT for Hate Speech Detection
This project experiments with many BERT variants to find the one that can best detect hate speech on social media. Tried BERT variants: BERT base, DistilBERT, RoBERTa base, DistilRoBERTa, RoBERTa large, BERTweet, and BERTweet large.

BGC NASA Landslide Detection
The goal of this project is to expand NASA's Cooperative Open Online Landslide Repository (COOLR) by automatically extracting landslide events from online sources.

The project consists of two parts:

1. News articles are extracted from online sources and then passed to a model that extracts the landslide's event properties.

2. The model extracts information from the articles: time, location, casualties, landslide category, and landslide trigger.


Python, C, SQL, C#, Swift, JavaScript, Java, PHP, HTML, Bash Script


Natural Language Toolkit (NLTK), SpaCy, PyTorch, TensorFlow, jQuery


Topic Modeling, Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT), Computational Linguistics, BERT, Long Short-term Memory (LSTM), Machine Learning, Artificial Intelligence (AI), Deep Learning, Artificial Neural Networks (ANN), Full-stack, Electrical Engineering, Text Classification, QA Testing, fastText, Deep Neural Networks, FastAPI, Scraping, Annotations, Custom BERT, Waveforms, Cisco, GPU Computing, Time Series, Signal Processing, Information Retrieval


Gensim, MATLAB, Geocoder


Data Science, Agile


Unix, Docker, Visual Studio Code (VS Code)



2021 - 2022

Master's Degree in Data Science

University of British Columbia - Vancouver, BC, Canada

2017 - 2021

Bachelor's Degree in Engineering

École de Technologie Supérieure - Montreal, QC, Canada