About Dorsaf
Passionnée par les technologies, l'automatisation, le fast prototyping et surtout l'innovation, j'ai impléménté plusieurs pipelines de dataops, mlops ETL pipelines et j'ai méné à bien end to end ML projetcs, j'ai une connaissance solide sur tout le scope Data ( statistiques, ML , Data engineering , ops )
Arabic
Native or bilingual
English
Fluent
French
Native or bilingual
Can work on-site
Paris (up to 50km)
Experience
- OVHCloudData EngineerTECHJanuary 2025 - Today (1 year and 5 months)Paris, FranceGeneral contextManage data quality and data governance for enterprise datasets, implementing a full DQ framework and metadatagovernance layer.• Implemented an end‑to‑end data quality framework using PySpark and Airflow (daily & monthly rules, scoring,reporting) and configuration of Alerting system.• Built and automated DataHub pipelines: ingestion, transformers, lineage extraction from Airflow, Spark and SQLoperators.• Defined and deployed dataset governance policies: domains, ownership, schema sensitivity tags and metadatastandardization.• Implemented data anonymisation rules (year‑level masking for personal attributes).• Integrated CI/CD for governance and quality workflows to ensure reproducibility across environments.
- Publicis MediaDATA ENGiNEERSeptember 2022 - December 2024 (2 years and 3 months)FranceGeneral context Manage the architecture, governance, and quality of media data. Organize, consolidate, and monitor the ingestion system of various data sources.• Development of Data models using SQL and make data available for Data Analysts/Dashboarding team in Big‑ query and scheduling the stored procedures for incremental loads.• Data Platform : Automating GCP ressources provisionning and Data pipelines of multi‑sources using Terraform with CI CD pipeline• Create monitoring pipelines from Alerting by mail using Cloud Functions in Python, Backup and Archiving to Data Observability.• Automating DAG in Snowflake using tasks.• Developement of MLops pipeline in Snowflake.• Development of attribution and contribution models using Shapley, logistic regression and markov chain.• Calling APIs such as Bings API and Facebook API for a specefic business report, in instance the auction insight report and scheduling an alerting for the nomenclature• R & D project for cookieless attribution and contribution using econometrics namely ARDL model.• Keywords Python, Bigquery, SQL, Snowflake, GCP , Terraform, Cloud Build, cloud scheduler, workflow, cloud functions, AdverityFreelance, Medix & Talentoday Remote, Client en US & France
- Freelance, DNAAfricaDATA ENGiNEER/ML ENGiNEER/DATA SCiENTiSTDecember 2020 - February 2021 (2 months)Mallard Point Remote non-electric canoe-in only campsite, Eyota, MN, USAGeneral context Development of a Lead Generation application using NLP and ML algorithms for the client.• Implementation of the backend architecture: scraping, storage in a Firebase NoSQL database, Flask and GCP APIs.• Deployment of the Python script in App Engine, configuration of resources (CPU, memory, readiness, liveliness) and real‑time maintenance.• Automating ETL pipelines running on an App Engine instance using Flask APIs: scraping, preprocessing, scoring, storing in Firebase and daily feedback loop through Cloud Scheduler vs cron jobs.• Creating a bucket in Cloud Storage for serialized ML models on a daily basis.• User feedback loop from the interface.• Developed variable extraction functionsformodelsfrom Tweets/Google Alerts (country, industry, company, prod‑ uct...)• Select, train, and evaluate the scoring models of the scrapped news (Catboost) and the classification models of the news category (NLP with TFIDF and Bi‑LSTM attention with Pytorch).
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Education
- ENGiNEERiNG DEGREE iN STATiSTiCS AND INFORMATiON ANALYSiSHigher School of Statistics and Information Analysis, ESSAIT2018ENGiNEERiNG DEGREE iN STATiSTiCS AND INFORMATiON ANALYSiS
- & PhysicsPreparatory Institute for Engineering Studies of El Manar& Physics