Resume

Professional Experience

Air France-KLM - Major airline group, European air transport leader Senior Data Scientist - Marketing Operations Research (Nov 2025 - Present)

• Contributed to ‘Offer Display Recommender’ project to personalize customer product offerings
• Designed and executed A/B tests to optimize customer journey and website experience, particularly for flight selection
• Analyzed customer behavior and translated insights into strategies/decisions for business stakeholders
• Impact: +0.6% CR and +0.5% ARPV improvement, driving €1M+ monthly incremental revenue

Mercor - Recruitment platform connecting talent with AI labs Mathematics/Statistics Expert (Aug 2025 - Jul 2026)

• Wrote mathematical problems to challenge reasoning capabilities of state-of-the-art language models (LLMs)
• Contributed to AI evaluation frameworks for leading research labs

Senzai - Data infrastructure and analytics startup, optimizing marketing campaigns Senior Data Scientist and Machine Learning Engineer - Pipelines and MLOps Lead (Oct 2023 - Oct 2025)

• Designed recommendation system to optimize customer targeting during digital marketing campaigns, increasing conversion rates by up to 30% across 3 million customers and 50 million interactions
• Designed and deployed data engineering modules and causal inference ML methods/models into production
• Established MLOps practices and scalable backend pipelines (GitLab CI/CD, Docker on AWS EC2, Kubernetes, Airflow, MLflow)

namR - Data intelligence startup specializing in buildings and energy transition Data Scientist - Geo & NLP Team (May 2023 - Oct 2023)

• Developed new features on large-scale datasets (up to 50 million rows on GCP)
• Optimized existing ML algorithms, reducing solar panel detection runtime from 25 to 8 hours

TotalEnergies One Tech - R&D branch of the French energy giant TotalEnergies Research Engineer - AI & Data Science R&D Program (Oct 2019 - Dec 2022)

• Developed Gaussian process regression models to predict gas well production (80% confidence)
• Developed causal inference models for geothermal wells, resulting in patent filing and three scientific publications
• Presented research advances to Digital Factory stakeholders, delivering actionable insights

Education

École Polytechnique, Institut Polytechnique de Paris (Oct 2019 - Dec 2022) PhD in Applied Mathematics - Specialization: Causal Inference and Uncertainty Quantification

• Dissertation: Statistical Learning and Causal Inference for Energy Production
• Published at ICML 2023 and Computational Statistics & Data Analysis Journal

École des Mines de Saint-Étienne (Sept 2016 - Sept 2019) Engineering Degree - Major: Data Science; Minor: Operations Research

• Focus: Supervised and Unsupervised Learning, Time Series, High Performance Computing, Multi-Objective Optimization

Université Paris-1 Panthéon Sorbonne (Sept 2018 - Sept 2019) M.Sc. in Mathematical Modelling and Methods in Economics and Finance

• Focus: Stochastic Calculus, Arbitrage Theory, Optimization, Credit Risk, Financial Markets

Skills & Competences

Mathematics & Statistics

Statistics, Machine Learning, Causal Inference, Optimization, Experimentation, Recommendation Systems, Bayesian Modeling, Uncertainty Quantification

Programming Languages

Python, R, SQL, MATLAB

Data Platforms & Infrastructure

• Cloud: Azure (TotalEnergies), GCP: BigQuery (namR, Air France-KLM), Vertex.ai (Senzai), AWS (Senzai)
• Databases: PostgreSQL, MySQL, Trino

Development Tools

VSCode, PyCharm, Jupyter Notebook, Jira, Linear, Atlassian, Confluence, Kanban, Dataiku DSS, Grafana

ML/Data Science Libraries

ggplot2, numpy, pandas, matplotlib, sqlalchemy, Scikit-learn, XGBoost, LightGBM, Shapely, CausalML, google-generativeai

MLOps & Production

Docker, Airflow, DVC, MLflow, GitLab CI/CD, Streamlit, FastAPI, PySpark, AWS EC2 and Redshift, Kubernetes

Summer Schools & Advanced Training

• August 2021: Machine Learning Summer School (MLSS) 2021 Taipei, Taiwan
• July 2021: Hi! PARIS Summer School 2021 on AI & Data for Science, Business and Society, Institut Polytechnique de Paris and HEC
• September 2020: Gaussian Process and Uncertainty Quantification Summer School, The University of Sheffield
• January 2020: Data Science, Optimization and Operations Research Winter School, École Polytechnique Fédérale de Lausanne

Awards & Recognition

Total-IMT Data Challenge Winner (2018)

• Won Kaggle-style competition using Random Forest algorithms
• Awarded research internship with TotalEnergies

Scholarships

• Study Abroad Grant (3,100€) - Moroccan Ministry of Higher Education (2020-2022)
• Government Merit Grant (15,500€) - Moroccan Ministry of Higher Education (2016-2019)

Download Resume

You can download a PDF copy of my resume here.