Naoufal Acharki
๐ About Me
Iโm a Senior Data Scientist and Machine Learning Engineer with a PhD in Statistics & Machine Learning from CMAP, รcole Polytechnique. I have more than 5 years of experience in Data Science and Machine Learning and currently working as a Founding Senior Machine Learning Engineer at Senzai. My expertise lies in developing data-driven solutions that combine statistical modeling, causal inference, and predictive modeling to solve complex business challenges.
๐ฌ Research Focus
My work focuses on developing innovative approaches that merge causality with machine learning for optimization and decision-making. Key areas include:
- Statistical Learning & Bayesian Modeling
- Causal Inference & Experimental Design
- Uncertainty Quantification
- Predictive Modelling
๐ผ Professional Journey
Senzai | Senior ML Engineer (Oct 2023 - Present)
- ๐ Leading development of CampAI, an intelligent campaign creation platform
- ๐ Implemented causal uplift modeling increasing conversion rates by 10-15%
- ๐ ๏ธ Architected end-to-end MLOps pipeline with GitLab CI/CD, Docker, and Airflow
namR | Data Scientist (May 2023 - Oct 2023)
- ๐๏ธ Enhanced building attributes algorithms using geospatial analysis
- โก Optimized solar panel algorithm reducing runtime from 25h to 8h
- ๐ Processed 50M+ building records using GCP BigQuery
TotalEnergies | R&D Data Scientist (Oct 2019 - Dec 2022)
- ๐ Completed Industrial PhD in Statistics & Machine Learning
- ๐ Published research on Causal Meta-Learners (ICML 2023)
- ๐ฎ Developed Gaussian Process models with 80% confidence in production predictions
- ๐ Led research on uncertainty quantification and causal inference
๐ ๏ธ Tech Stack
Core Technologies
- Languages: Python, R, SQL, LaTeX
- ML/AI: Scikit-learn, PyTorch, CausalML, EconML
- LLM & GenAI: Gemini, Vertex.AI, OpenAI
- Data Processing: Pandas, NumPy, GeoPandas
- Visualization: Matplotlib, Seaborn, ggplot2
Infrastructure & Tools
- MLOps: Docker, Airflow, MLflow, DVC, GitLab CI/CD
- Cloud: AWS, GCP (BigQuery), Azure
- Databases: PostgreSQL, MySQL
- Development: VSCode, PyCharm, Jupyter, Git
๐ GitHub Stats
๐ GitLab Analytics
Tickets, merge requests, pushes and comments from February 2024 to February 2025
๐ Featured Publications
| Title | Conference | Year | Link |
|---|---|---|---|
| Comparison of meta-learners for estimating multi-valued treatment heterogeneous effects | ICML paper | 2023 |  |
| Statistical Learning and Causal Inference for Energy Production | PhD Thesis | 2022 |  |
| Robust prediction interval estimation for Gaussian processes by cross-validation method | JSDA Journal | 2022 |  |
๐ Awards & Honors
- Total-IMT Data Challenge Winner (2018)
- Won Kaggle-style competition using Random Forest algorithms
- Awarded internship with TotalEnergies
- Scholarships and Grants
- Study Abroad Grant (3,100โฌ) - Moroccan Ministry of Higher Education (2020-2022)
- Government Merit Grant (15,500โฌ) - Moroccan Ministry of Higher Education (2016-2019)
๐ค Selected Talks & Conferences
International Conferences
- ICML 2023 - Honolulu, Hawaii, USA
- Presented โMeta-Learners for Multi-Valued Heterogeneous Effectsโ
- SIAM UQ22 - Atlanta, USA
- Presented โRobust Prediction Interval Estimation for Gaussian Processesโ
Invited Talks
- University of Bern, Bern, Switzerland
- Seminar on Gaussian Processes for Optimization
- Ionian University, Corfu, Greece
- Greek Stochastics ฮผโ: Causal Learning
- INRIA Saclay & LISN, Gif-Sur-Yvette, France
- The Causal TAU seminar
- National Taiwan University, Remote
- Machine Learning Summer School MLSS 2021
๐ค Letโs Connect
Feel free to reach out for collaborations or just to say hi!