Madriss is available for hire

Madriss Seksaoui

Verified Expert in Engineering

Data Scientist and Machine Learning Developer

Paris, France

Toptal member since January 11, 2022

Expertise

Machine Learning Artificial Intelligence (AI)Data Science Deep Learning Python Pandas TensorFlow Scikit-learn Keras Algorithms Statistics Data Analysis Machine Learning Operations (MLOps)Time Series

Bio

Madriss is a dedicated data scientist and machine learning engineer who has six years of professional experience analyzing data, building, deploying, and managing the lifecycle of machine learning models. He has worked in various industries, including email, digital marketing, insurance, and edtech. Currently focusing on healthcare, Madriss is eager to work among the best talents on the most challenging projects.

Portfolio

L'écran du savoir

Artificial Intelligence (AI), Machine Learning, Deep Learning...

Stago Group

Artificial Intelligence (AI), Data Science, Deep Learning, Docker...

CNP Assurances

Artificial Intelligence (AI), Computer Vision, OCR, OpenCV, Tesseract, Keras...

Experience

Artificial Intelligence (AI) - 6 years Data Science - 6 years Machine Learning - 6 years Deep Learning - 5 years Scikit-learn - 5 years TensorFlow - 5 years Python 3 - 5 years Generative Pre-trained Transformers (GPT) - 3 years

Availability

Part-time

Preferred Environment

Python 3, TensorFlow, PyTorch, Git, Machine Learning, Deep Learning, PySpark, SQL, Azure, Databricks

The most amazing...

...project I've worked on consisted of developing an AI-based rejection filter aiming to improve the analytical performances of medical instruments.

Work Experience

Data Scientist

2022 - PRESENT

L'écran du savoir

Developed a deep learning model based on semantic similarity to determine students' answer marks with respect to a reference answer.
Implemented a zero-shot classification pipeline for tagging questions.
Developed a recommender system to increase student engagement by proposing questions and exercises relevant to their level.

Technologies: Artificial Intelligence (AI), Machine Learning, Deep Learning, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Python, Data Science, Data Science, Algorithms, PyTorch, SQL, MySQL, Pandas, Frameworks, Generative Artificial Intelligence (GenAI), Large Language Models (LLMs)

Data Scientist | Machine Learning Engineer

2018 - PRESENT

Stago Group

Improved signal classification and regression algorithms in the context of a patent application for a new methodology to determine and identify anticoagulant drugs.
Implemented a deep learning model to aid in diagnosing thrombophilia using thrombin generation curves. Analyzed clinical data, including an exploratory phase and statistical tests, and interpretability of models.
Implemented a multi-stage anomaly detection system using deep learning models trained to extract features from biological test signals and various anomaly detection algorithms.

Technologies: Artificial Intelligence (AI), Data Science, Deep Learning, Docker, Machine Learning, Data Visualization, Keras, Time Series, Python, Data Science, Algorithms, PyTorch, SQL, Machine Learning Operations (MLOps), MySQL, Team Leadership, Pandas, Computer Vision Algorithms, Computer Vision, Image Recognition, Frameworks, Generative Artificial Intelligence (GenAI), Large Language Models (LLMs)

Data Scientist | Computer Vision Engineer

2018 - 2018

CNP Assurances

Improved the optical character recognition system (OCR) used to extract texts from the RIB and scanned checks.
Developed tools for parsing certain fields, such as last name, first name, address, and others.
Deployed the OCR tool as a standalone REST API service.

Technologies: Artificial Intelligence (AI), Computer Vision, OCR, OpenCV, Tesseract, Keras, Python, Data Science, Machine Learning, Data Science, Algorithms, SQL, MySQL, Pandas, Computer Vision Algorithms, Image Recognition, Frameworks

Data Scientist

2017 - 2018

Natexo Group

Developed a machine learning solution to optimize email marketing campaigns, allowing the increase of opening rates.
Developed multi-modal deep learning models using TensorFlow to judge the attractiveness of a marketing campaign using visual and text inputs.
Implemented interactive dashboards with Plotly and Dash.

Technologies: Artificial Intelligence (AI), Deep Learning, Machine Learning, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Data Visualization, Python, Data Science, Data Science, Algorithms, SQL, MySQL, Pandas, Frameworks

Experience

Skin Lesion Identification Based on Dermoscopic Images

https://github.com/madriss/Dermoscopy-CNN

This Python-based app loads a fine-tuned EfficientNet model trained to identify various skin lesions from dermoscopic images. The model can identify melanomas, melanocytic nevus, basal cell carcinoma, actinic keratosis, Bowen’s disease, different types of benign keratosis, dermatofibroma, and vascular lesions.

Breast Cancer Detection Using Histological Slices

https://github.com/madriss/Breast_Cancer_Detection-Histopathology

This Python and Flask-based app classifies slices to detect breast cancer tissues vs. normal tissues. The app loads a fine-tuned EfficientNet model and implements Grad-CAM heatmaps to display the most relevant zones in the slice according to the model. The app was built using a Dockerfile and deployed on Google Cloud Platform (GCP).

French IBAN Retriever Using OCR

https://github.com/madriss/ocr_demo

This small Python-based optical character recognition (OCR) project uses the Tesseract API to extract French IBANs from scanned photos. The app was built using the Streamlit framework and deployed on GCP.

Education

2016 - 2017

Master's Degree in Data Science

CentraleSupélec | Paris-Saclay University - Paris, France

2015 - 2016

Master's Degree in Finance

Paris-Panthéon-Assas University - Paris, France

2012 - 2015

Bachelor's Degree in Finance

Paris-Panthéon-Assas University - Paris, France

Certifications

MAY 2020 - PRESENT

AI for Medical Prognosis

Coursera

APRIL 2020 - PRESENT

AI for Medical Diagnosis

Coursera

MARCH 2020 - PRESENT

Browser-based Models with TensorFlow.js

Coursera

MARCH 2019 - PRESENT

TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

Coursera

JUNE 2018 - PRESENT

Convolutional Neural Networks

Coursera

APRIL 2016 - PRESENT

Statistical Learning

Stanford University | via Coursera

JANUARY 2016 - PRESENT

Big Data Foundations

IBM

JANUARY 2016 - PRESENT

Foundations of Strategic Business Analytics

ESSEC Business School | via Coursera

DECEMBER 2015 - PRESENT

Machine Learning Foundations: A Case Study Approach

Coursera

Skills

Libraries/APIs

TensorFlow, Scikit-learn, Keras, Pandas, PyTorch, OpenCV, PySpark

Tools

Git

Languages

Python 3, Python, SQL

Platforms

Ubuntu, Docker, Google Cloud Platform (GCP), Azure, Databricks

Storage

MySQL

Frameworks

Flask

Other

Machine Learning, Deep Learning, Data Science, Artificial Intelligence (AI), Data Science, Statistics, Data Analysis, Time Series Analysis, Convolutional Neural Networks (CNNs), Natural Language Processing (NLP), Time Series, Generative Pre-trained Transformers (GPT), Algorithms, Machine Learning Operations (MLOps), Frameworks, Big Data, Analysis, Computer Vision, OCR, Tesseract, Deployment, Data Visualization, Team Leadership, Computer Vision Algorithms, Image Recognition, Generative Artificial Intelligence (GenAI), Large Language Models (LLMs)

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