Freelancer profile translated to English.
Back to original languageAbout Alaeddine
🎯 Senior Data Scientist specialized in Data Marketing
Are you looking for a Data Science expert to transform your data into decision-making levers and optimize your marketing and business performance?
As a Senior Data Scientist, I assist my clients in measuring and optimizing their marketing investments through robust models, actionable analyses, and clear dashboards.
I have over 5 years of experience in various environments (Start-ups, Consulting, Large Corporations).
💡 My expertise covers
- Data analysis
- Marketing modeling and sales forecasting (Marketing Mix Modeling)
- Machine Learning & Deep Learning modeling
- Visualization and communication of insights
🔹 Technical Stack/Skills
I use daily:
- Python & SQL for analysis, modeling, and deployment of Data Science solutions.
- Clouds (GCP & Azure) for industrialization and scalability of projects.
- Snowflake & DBT for data preparation, transformation, and database management.
- Airflow for automation and orchestration of data pipelines.
- Dataiku to accelerate prototyping and collaborate effectively with business teams.
Ready to boost your Data projects?
Contact me for an initial discussion. Let's schedule a call to discuss your needs and see how I can help you achieve your goals through data.
French
Native or bilingual
English
Fluent
Can work on-site
Paris (up to 50km), Lyon (up to 50km), Bordeaux (up to 50km), Marseille (up to 50km), Lille (up to 50km)
Experience
- Pernod RicardSenior Data ScientistWINE AND SPIRITSNovember 2023 - Today (2 years and 9 months)Paris, FranceI work as a Data Scientist on the Matrix project, which aims to help marketing teams optimize their campaigns and budget allocation, based on the different brands and advertising channels present in their market.My ContributionAs a Data Scientist for the German and British markets of Matrix, my role was to maintain and update a Marketing Mix Model (MMM) with fresh data every 6 months.This allows us to describe what happened in previous campaigns, in order to obtain recommendations for future marketing budgets.Missions
- Contribute to data collection and preparation as input for the model.
- Analyze data and interact with Data Analysts and Marketing Effectiveness Leads to validate data.
- Retrain several Marketing Mix Models with new data.
- Analyze and present the best model to the marketing teams.
- Maintain and improve the tools and applications used internally by Data Scientists.
Results- Reduction of marketing budget by -13% while improving ROS (Return On Spend: +11%)
- Automation of the data retrieval and preparation phase.
- Improvement of the model results analysis tool (Streamlit application).
Technical Stack- Python, SQL, Snowflake, Databricks, DBT, Streamlit
- Cloud: Microsoft Azure
- Project Management: JIRA, Notion, Excel
- namRTech LeadENERGY AND UTILITIESMarch 2023 - November 2023 (8 months)Paris, FranceWorking with the business lead, I oversaw the progress of the team's projects, which involved producing all the necessary data to estimate the solar potential of every roof in France.Missions
- Estimate the human and technical resources needed for the project
- Establish technical feasibility and create a schedule
- Answer technical questions to make choices and ensure project progress
- Implement team rituals to keep all Squad members informed
- namRData Scientist & Computer Vision ScientistENERGY AND UTILITIESOctober 2019 - February 2023 (3 years and 4 months)Paris, FrancenamR is a startup founded in 2017 that produces data to create a digital twin of the French territory.This data allows namR's clients to create value and accelerate the energy renovation of their real estate properties.Data can be aggregated and cleaned from open data sources or from namR's partners. It can also be produced/completed using Machine Learning and Deep Learning.My ContributionI actively participated in data production projects, whether:
- with structured data (Machine Learning)
- with unstructured data (Computer Vision / Deep Learning)
I also contributed to the maintenance and improvement of the geocoding tool, which converts textual addresses into geolocated points.Missions- Update the prediction model for roof types and materials (Deep Learning on aerial images) following the update of aerial imagery and the acquisition of new labeled data.
- Develop an object detection model for roofs (Instance Segmentation).
- Update namR's address repository to have a more complete and actionable address base.
- Improve the address geocoding tool.
- Explore R&D topics. Example: Mixing structured and unstructured data as input for an ML / Computer Vision model.
- Package a solution for analyzing the errors of a Deep Learning model using object-oriented programming.
- Use the Dataiku API to interact with trained Machine Learning models for scoring and error analysis.
Technical Stack- Python & PostgreSQL
- Dataiku
- QGIS
Google Cloud Platform (GCP)- Cloud Storage → storage of aerial images
- Pub/Sub & Cloud Functions → industrialization of inference models
- AutoML Vision → labeling and annotation of images
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Education
- Engineering DegreeTelecom SudParis20193 ans de cycle d'ingénieurs Cours d'approfondissement - Apprentissage statistique - Data Mining - Théorie de Sondage - Optimisation - Séries temporelles - Processus Stochastiques - Chaînes de Markov - Économétrie - Finance Quantitative - Probabilités / Statistiques
- CPGE MPSI/MP*Lycée du Parc2016Cours - Maths - Physique - Informatique