Ayoub Abraich

Evry, France • abraich.jobs@gmail.com • ayoubabraich.netlify.app

Data Scientist | AI Research Engineer | PhD Candidate

Experienced Data Scientist and Python Expert with a PhD in Data Science and a Master's in Data Science. Proven track record of over 4 years in data analysis, machine learning, deep learning, and causal inference, specializing in healthcare and finance. Proficient in Python (PyTorch/TensorFlow) and adept at code reviews. Eager to contribute expertise to impactful projects and open to collaborative opportunities for continuous learning.

Education

PhD in Data Science: Deep Learning Applications for Causal Treatment Effect Estimation in Longitudinal Context
  • Paris-Saclay University • 09/2020 - 2023
    • Research Area: Causal Inference, Survival Analysis, Representation Balancing
    • Relevant Publications:
      • "Theoretical Guarantees for Representation Balancing in Survival and Classification Causal Inference with Multiple Treatment Lines" (Preprint, November 2023)
      • "SurvCaus: Representation Balancing for Survival Causal Inference" (Preprint, March 2022, 10+ citations as of April 2024)
      • Other publications on my ResearchGate.
    • Scholarships and Funding:
      • PhD Bourse (FMJH and EDMH): €57,000 net over 3 years (2020-2023)
      • FMJH (Fondation Jack Hadamard) Excellence Bourse: €14,000 (2018-2020)
      • OCP Bourse Excellence: €6,000 (2016)
Master's degree (M1- M2) in Data Science - Finance
  • Paris-Saclay University • GPA: Major • 09/2018 - 10/2020
    • Completed rigorous AI coursework covering Reinforcement Learning, Deep Learning, and Computational Statistics.
    • Applied advanced techniques in GANs for practical data applications.
    • Demonstrated expertise in Scientific Python, R, and GPU computing for AI-driven solutions.
Bachelor's degree in Applied Mathematics (3 years)
  • Université d'Evry-Val d'Essonne • GPA: Major • 08/2015- 09/2018
    • Completed a 3-year Bachelor's program in Applied Mathematics, including 2 years of CPGE (Preparatory class for high schools in Mathematics and Physics).
    • Acquired a strong foundation in mathematical principles, advanced probability, statistics, and programming skills (C, Python, R).
    • Specialized in advanced mathematics during academic pursuits.

Work Experience

AI Research Scientist & PhD Candidate | LaMME | Evry, France | Full-time | 04/2020 - 2023
  • Led creation and deployment of advanced deep learning models for causal effects, utilizing PyTorch and TensorFlow.
  • Conducted pioneering research in causal inference, enhancing predictive accuracy in complex data landscapes.
  • Implemented domain adaptation strategies, optimizing model performance across diverse domains.
  • Played a key role in cross-functional collaboration, designing experiments, analyzing outcomes, and providing actionable insights.
  • Innovated methodologies for integrating causality into deep learning models, advancing industrial applications.
Data Scientist Freelancer | Malt | Upwork | Paris, France | Part-time | 09/2019 - Present
  • Data Analysis and Visualization: Applied advanced statistical techniques to distill meaningful insights from intricate datasets. Translated findings into compelling visualizations for actionable outcomes.
  • Machine Learning and Predictive Modeling: Designed and implemented machine learning models, leveraging classification, regression, and clustering algorithms to optimize decision-making processes and solve business challenges.
  • Python Programming: Proficiently utilized Python for data manipulation, analysis, and model implementation. Demonstrated expertise in libraries such as Pandas, NumPy, Scikit-learn, PyTorch, and TensorFlow.
  • End-to-End Solution Development: Successfully implemented end-to-end solutions using frameworks like Flask, ensuring seamless integration and deployment of data science applications.
  • Client Collaboration: Effectively engaged with clients, comprehending unique requirements, and delivering tailored solutions that align with specific business objectives.
  • Project Management: Successfully oversaw end-to-end project lifecycles, from scoping and planning to execution and delivery. Ensured timely and high-quality outcomes.
Data Scientist | DRL | CMAP Ecole Polytechnique | Palaiseau | 04/2019 - 07/2019
  • Collaborated with Professor Eric Moulines on pioneering research for "Visually Grounded Question Answering" (VGQA), implementing cutting-edge deep reinforcement learning algorithms.
  • Focused on enhancing dialogue generation by synergizing visual information and natural language understanding, achieving coherent and contextually relevant responses to visually grounded queries.
  • Contributed to academic discourse through valuable insights and methodologies, pushing the boundaries of knowledge at the intersection of deep learning, reinforcement learning, and natural language processing.

Skills

Programming Languages: C++, HTML, JavaScript, Python, R, SQL
Tools and Frameworks: AWS Sagemaker, Azure, Django, Docker, FastAPI, Flask, Heroku, Linux, PySpark, PyTorch, Streamlit, TensorFlow
Advanced Modeling and MLOps: Automating MLOps for Deep Learning, Designing Experiments, Implementing Advanced Statistical Modeling
Knowledge Areas: Algorithmic Trading, Causal Inference, Computer Vision, Deep Learning, Generative Adversarial Networks (GANs), Machine Learning, Natural Language Processing (NLP), Optimization, Reinforcement Learning, Statistics, Time Series Analysis
Data-related Skills: BeautifulSoup (BSoup), Data Scraping, Postman, PySpark, REST APIs, Scrapy
Business Problem Solving: Data Mining, Solving Business Problems through ML, Statistical Algorithms
Large Data Sets and Distributed Computing: Distributed Computing, Optimization, Proficient in Working with Large Data Sets, Simulation
Languages: French (Fluent), Proficient in English

Certifications

  • Machine Learning pour le trading de A à Z, Data World • 06/2020
  • Spécialisation Deep Learning, DeepLearning.AI • 01/2019
  • Machine Learning, Stanford University • 06/2018 - Present