Freelancer profile translated to English.
Back to original languageAbout Mouad
Graduated as an engineer in Scientific Computing and Data Science from the Higher Institute of Informatics, Modeling and their Applications (Clermont-Ferrand), and Polytechnic University of Catalonia (Barcelona), as part of a double degree (Master in Data Science), with a wide range of experience in Machine Learning / Data Engineering.
In 2017, I decided to take on new challenges by becoming self-employed. During my first two-year mission at SINTEF, in collaboration with The Norwegian Petroleum, I was responsible for creating a biometric identification system based on brain activity. I also worked on setting up and improving data integration pipelines, automating the containerization of certain applications, signal processing, and reporting.
My last one-year mission at TriM (Turin and Paris) was to support the Austrian Sailing Federation in collecting, organizing, managing, analyzing, and interpreting meteorological, geographical, and strategic data in Japan, to strengthen the decision-making process during sailing and racing.
Areas of expertise:
• Big Data (Hadoop, Spark, Java, Scala, Cloud...)
• Machine Learning (Clustering, Regression, Scikit-learn, Caret...)
• Deep Learning (NLP, Object Detection, Tensorflow/Keras, PyTorch...)
• Business Intelligence (ETL, Reporting, Dashboard, PowerBI, Talend...)
French
Native or bilingual
English
Fluent
Remote only
Primarily works remotely
Experience
- DecathlonData EngineerSPORTSJanuary 2023 - Today (3 years and 5 months)Paris, FranceExpert in developing robust and scalable data solutions. With extensive experience atDecathlon**, I designed and deployed a complete **Data Qualitysolution from **A to Z**, used by several teams on the Data platform.- Data & Cloud Architecture
- Design of optimized storage architectures on S3.
- Migration and adaptation of solutions between EMR and Databricks.
- Implementation of data pipelines with Airflow (development of custom operators).
- Expert Great Expectations: contribution to the open-source project (PR accepted v0.17.23).
- OpenLineage integration for data lineage and monitoring
- Exploration and documentation of alternative solutions (Deequ, DBT-expectations, Elementary).
- Development & DevOps- Dynamic and configurable PySpark jobs.
- Multi-platform Dockerization (amd64/arm64).
- CI/CD and template management with cruft.
- Key Achievements- End-to-end Data Quality Solution: Development of a first functional version in 1 sprint, followed by continuous improvement with 30+ features added.
- Open-source contribution: Resolution of a critical issue regarding verbosity for PII data in Great Expectations, with direct collaboration with the core team.
- Team Enablement: Successful onboarding of 3+ teams, creation of detailed documentation and tools facilitating adoption (Databricks notebooks for rule editing).
- Technical Innovation: Development of custom expectations, integration of cryptography for sensitive data.
- Working Approach- Solution-oriented: Ability to overcome complex technical challenges and propose innovative architectures.
- Continuous Improvement: Constant iterations based on user feedback.
- Documentation & Sharing: Creation of detailed guides and presentation of solutions to teams.
- Technological Watch: Regular exploration of new libraries and best practices.
- Société GénéraleData EngineerBANKING AND INSURANCESeptember 2020 - March 2023 (2 years and 6 months)Fontenay-sous-Bois, FranceAs a Data Engineer, I ensure access to data sources and data, and work on all activities related to the Financial Department:- Implement all techniques and processes for collecting, cleaning, organizing, synthesizing, and effectively modeling data (especially for feeding the Datalakes it sets up and the Big Data projects it supports).- Provide analytical support for conducting complex data exploration and analysis from various sources.- Participate in the industrialization of the process for the most relevant data within the project framework to produce the most operational analyses.- Work in close collaboration with Data Architects and Business Teams...- Develop BI Dataviz solutions in compliance with the agile methodology of the Smart data unit.- Participate in the application and continuous improvement of the Smart Data unit's procedures.- Ensure the run and maintenance of solutions within the Smart Data scope.- Maintain technological watch and participate in POCs and Hackathons related to my activities.- Participate in the integration of new data engineers in the team.
- TriM_Translate Into MeaningData ScientistSPORTSOctober 2019 - August 2020 (11 months)Turin, ItalySupport the Austrian Sailing Federation in collecting, organizing, managing, analyzing, and interpreting meteorological, geographical, and strategic data to enhance decision-making during sailing and racing:• Use of Clustering algorithms to better understand the different characteristics of the wind.• Automatic generation of results and visualized data in PDF format.• Interaction with the Austrian sailing team to meet specific feature requirements.
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Education
- Computer Science Engineering DegreeHigher Institute of Informatics, Modeling and their Applications2019Cours: Structures de données et algorithmes, stabilité et optimisation mathématiques, statistiques et processus aléatoires, probabilité et inférence statistique, algèbre linéaire et équations différentielles, théorie des graphes, recherche opérationnelle, réseau et vision par ordinateur, C/C++, UML, Matlab, QNAP , Pandas, Java, Apprentissage automatique, Big Data, SQL.
- Master in Data ScienceUniversitat Politècnica de Catalunya2020Cours: Statistical Modeling and Design of Experiments (SMDE), Data Warehousing (DW), Kernel-Based Machine Learning and Multivariate Modeling (KMLMM), Open Data (OD), Algorithmics for Data Mining (ADM).
Certifications
- Convolutional Neural Networksdeeplearning.ai2020
- Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimizationdeeplearning.ai2020