Freelancer profile translated to English.
Back to original languageAbout Jonathan
Senior Data Analyst with over 7 years of experience, I design data solutions that have a direct impact on business performance. My background has led me to work on various projects — econometric modeling, recommendation systems, loyalty program redesign — leveraging a modern technical stack: SQL, Python, dbt Cloud, and BigQuery (Google Cloud Platform). What sets me apart is my ability to cover the entire data transformation chain, from data modeling to analytical reporting, while keeping the business at the center. I am currently seeking a mission in Data Analysis, Analytics Engineering, or BI Engineering in an environment where data is a true lever for decision-making.
French
Native or bilingual
English
Fluent
Can work on-site
Paris (up to 50km), Annecy (up to 50km), Aix-en-Provence (up to 50km), Lyon (up to 50km)
Experience
- alineaSenior Data Analyst - Marketing Mix ModelingRETAIL (LARGE RETAILERS)October 2025 - January 2026 (3 months)Aix-en-Provence, FranceAs part of an effort to optimize marketing investments for an omnichannel retailer (€225M in revenue), I designed an end-to-end Bayesian Marketing Mix Modeling model, covering all of the brand's marketing channels over a four-year historical period (2021–2025).
- **Analysis**: Data collection and cleaning. Analysis of KPIs for each channel — costs, impressions, and GRP — across the entire media mix: Social Media Ads (SMA), Search (SEA), VOL, display, Out-Of-Home (OOH), radio, and TV.
- **Modeling**: Weekly granularity on revenue, Bayesian model. Carryover effects (adstock, persistence of advertising impact over time) and saturation effects (diminishing returns) were considered. Consideration of the commercial animation plan.
- **Deliverables**: Python-documented Bayesian MMM model, weekly data structuring by channel (costs, impressions, GRP), attribution report by channel, budget scenario simulation tool, presentation of recommendations to the marketing department.
- **Result**: Precise quantification of each channel's contribution — marketing investments were attributed ~9% of total revenue.
- alineaAnalytics Engineer - Loyalty Program RedesignRETAIL (LARGE RETAILERS)November 2024 - July 2025 (8 months)Aix-en-Provence, FranceAs part of the complete redesign of a loyalty program for an omnichannel retailer (35 stores + e-commerce), I played a central role in both data modeling and application architecture consulting.
- **Modeling**: Responsible for the complete modeling of the program logic in SQL via dbt Cloud: calculation of points earned on each multichannel purchase (web, store), management of tiers and privileges, generation of benefit eligibility, and application of burn rules. Consideration of edge cases — canceled purchases and returns. Implementation of dbt snapshots to historicize the evolution of points and customer statuses, allowing for precise tracking of individual journeys and auditability of calculations.
- **Architecture**: Support for technical teams on inter-application architecture issues and the transmission of loyalty data between the company's various systems (CRM, point of sale, web, API, marketing).
- **BI**: Development of a dedicated monitoring dashboard to continuously track program KPIs: activation rate, privilege burn, customer status evolution, and redemption behaviors.
- **Data Stack**: dbt Cloud environment connected to BigQuery (GCP) structured with development and production environments for better deployment reliability. dbt Cloud jobs orchestrated by Apache Airflow Cloud Composer (GCP).
- **Deliverables**: Set of documented and industrialized dbt models in dev/prod environments, customer data historization snapshots, handling of edge cases (cancellations, returns), documentation of data architecture and inter-application flows, program monitoring dashboard.
- **Result**: Program in production, contributing to 1.7% of incremental revenue.
- alineaSenior Data Analyst - Cross-sell Analysis and Recommendation SystemRETAIL (LARGE RETAILERS)June 2024 - October 2024 (4 months)Aix-en-Provence, FranceDesign and deployment of a personalized product recommendation engine, from purchase behavior analysis to integration into email campaigns.
- **Analysis**: Sequential pattern mining and product association rules to calculate confidence and lift metrics. (Python)
- Internal **Adoption**: Creation of a Plotly Dash application (Python) for marketing and product teams, allowing simulation of purchase baskets and exploration of recommendations generated by the engine.
- **Deliverables**: Python purchase behavior analysis pipeline (sequential pattern mining + association rules), industrialized multi-criteria recommendation engine, Plotly Dash application for simulation and exploration for marketing and product teams, integration into email campaigns, and performance tracking dashboard.
- **Result**: +38% CTR (4.3%) and +54% conversion rate (0.62%) vs. existing proprietary solution.
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Education
- Finance and InsuranceEcole Centrale Marseille2017
- Master's Degree, Economist EngineerAMSE2017Programme sélectif et spécialisé combinant ingénierie, économie, and analyse quantitative.