Freelancer profile translated to English.
Back to original languageAbout Majdi
Experienced Data Engineer and Visionary Entrepreneur
With over 8 years of expertise as a data engineer, I have led innovative technological initiatives for dynamic startups such as The Python Quants and Capitalab in Fintech, Fairphonic in MusicTech, Lemlist, as well as for renowned multinational corporations like Givaudan.
In 2019, I took a decisive step by founding my own company. Under my leadership, we developed cutting-edge audio recognition models, which are now adopted by prominent players in the music industry.
My unique background, at the intersection of entrepreneurship, data science, and project management, has equipped me with rare versatility. I am equally comfortable with in-depth technical design, team management, and strategic decision-making.
Technical Skills
- Languages & Tools: Python (8+ years), SQL (8+ years), Github, Docker.
- Platforms & Technologies: Dbt, Snowflake/BigQuery, Dataiku, Google Cloud, AWS, Airflow.
- Full mastery of the Data software production chain for 8 years.
Professional Strengths
Proven ability to lead large-scale projects, ensuring flawless execution.
Aptitude to serve as a bridge between Tech and Business teams, ensuring that technical vision and business objectives remain aligned. I am deeply aware of the importance of clear communication, knowing that any deviation can impact the product and, by extension, revenue.
I am passionate about bringing my extensive expertise and leadership to ambitious projects that seek to push the boundaries of technology and innovation.
French
Native or bilingual
Arabic
Native or bilingual
English
Native or bilingual
Can work on-site
Paris 19e Arrondissement (up to 50km)
Experience
- lemlistSenior Analytics EngineerDIGITAL AND ITOctober 2023 - Today (2 years and 10 months)Paris, FranceImplementation of a robust data architectureto centralize and structure data from various sources, enabling reliable analysis and data-driven decision-making.Creation and optimization of dashboardsto provide teams with real-time key performance indicators, facilitating goal tracking and strategic alignment.Deployment of artificial intelligence (AI) models, including large language models (LLMs), to automate advanced analytics and generate predictive recommendations tailored to team needs.Analysis of customer and marketing datato identify trends, segment audiences, and optimize campaigns based on collected insights, thereby increasing the effectiveness of actions.Collaboration with product and marketing teamsto align data and AI usage with business objectives, ensuring a measurable impact on growth and customer acquisition.
- Givaudan Digital FactoryData Analyst / Data EngineerLUXURY GOODSSeptember 2021 - December 2022 (1 year and 4 months)Paris, FranceBig Data InfrastructureSetup of a complete infrastructure with Snowflake for data storage and management, Airflow for workflow orchestration, and Dataiku for data processing and visualization.Data ScrapingUse of Python to efficiently extract data from providers, ensuring reliable and systematic collection.ETL PipelineDesign of a robust pipeline for data processing, cleaning, and loading, ensuring its integrity and availability for analysis.Integration into an internal and secure databaseTransfer and integration of prepared data into a Postgres database, followed by the creation of user-friendly visualizations.
- Behind the appData AnalystE-COMMERCENovember 2022 - December 2022Paris, FranceSQL ExploitationAdvanced use of SQL to directly query Stripe data, enabling in-depth analysis and custom queries to meet specific business needs.Query OptimizationDesign of efficient SQL queries to quickly extract relevant information, reducing response time and improving report efficiency.Data VisualizationFormatting of obtained results to create clear and understandable visualizations on Looker Studio, facilitating decision-making for stakeholders.Report AutomationConfiguration of reports to run at regular intervals, ensuring stakeholders receive updates in real-time or on a defined schedule.Team CollaborationWorked closely with finance and operations teams to understand their specific needs, ensuring that the provided reports were relevant and useful.
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Education
- Master in Applied Probability and StatisticsNational University of Singapore2017Formation en deux étapes 1) Cours de Machine Learning, Data Mining, Analyse de Graphes, Ingénierie Financière 2) Thèse de Master portant sur les "Numerical Methods for Backward Stochastic Differential Equations"
- Engineering Graduate SchoolENSTA Paris2017Maths Appliquées à la finance avec notamment du - calcul stochastique - chaînes de Markov - Pricing de dérivées - Traitement du Signal - Science des Données - Optimisation