About Alexandra
J’aide les entreprises à structurer, modéliser et exploiter leurs données pour prendre de meilleures décisions, plus rapidement.
Je construis des pipelines ELT robustes, des modèles analytiques maintenables avec dbt, et des dashboards pertinents avec BI (Tableau / Power BI / Looker).
👉 Services proposés :
• Architecture de données & modern data stack
• Modélisation et tests avec dbt
• Intégration et ingestion de données (APIs, pipelines)
• Analyse exploratoire & définition de KPI business
• Visualisation & insights opérationnels
English
Native or bilingual
French
Native or bilingual
Italian
Conversational
Can work on-site
Paris (up to 50km)
Experience
- ProjetData Team Lead | Customer Support Performance Analytics – AI Chatbots vs Human Agents (DBT & Looker)E-COMMERCEDecember 2025 - December 2025Context & ObjectiveData-driven evaluation of AI chatbots vs human customer support to support strategic decisions on service optimization and cost reduction.Delivery
- Designed and implemented an end-to-end analytics pipeline (multi-source ingestion, transformation, modeling).
- Built a dbt modeling layer (staging → marts) to unify operational, cost, and satisfaction data.
- Modeled KPIs covering performance, cost efficiency, CSAT, and operational scalability.
- Developed an interactive Looker Studio dashboard with drill-downs to support decision-making.
- Delivered a decision framework identifying optimal use cases for AI vs human agents.
Key Insights- AI outperforms human agents on low-complexity, high-volume interactions (response time & cost).
- Human agents remain critical for complex, emotional, or high-value cases.
- Hybrid support model enables significant cost reduction while preserving customer satisfaction.
Expected Business Impact- Up to 5× faster response times on targeted categories
- Up to 2× cost reduction on low-complexity interactions
- Improved agent productivity
- Potential +0.10 CSAT uplift
- ProjetAnalytics Engineer | Data Pipeline & BI Project (dbt modelling)E-COMMERCENovember 2025 - December 2025 (1 month)Context & ObjectiveDesign and implementation of an analytics layer to consolidate marketing acquisition and e-commerce sales data in order to monitor campaign profitability and financial performance.Delivery
- Centralized multiple marketing acquisition sources (Google Ads, Bing, Criteo, Facebook) with sales, product, and shipping data.
- Built a dbt modeling layer including staging, intermediate, and marts models.
- Designed daily and monthly financial models to track costs, revenue, margins, shipping, and ROI.
- Delivered finance-focused data marts enabling campaign-level and global profitability analysis.
Data Quality & Documentation- Implemented dbt tests (unique, not_null) on key identifiers.
- Set up relationships tests between marketing sources and sales data.
- Added consistency checks on dates and financial amounts.
- Documented models to ensure maintainability and scalability.
Key Outcomes- Harmonization of 4 heterogeneous marketing data sources.
- Automated margin calculation per order.
- Consolidated view across acquisition, sales, and finance.
- Delivery of a ready-to-use financial data mart for BI and reporting.
- Réseau Vrac & RéemploiProgram Manager - Performance & OperationsMarch 2021 - April 2025 (4 years and 1 month)
- Définition, structuration et suivi de 20+ KPI opérationnels (volumes consignés, taux de retour, coûts logistiques, performance).
- Conception et maintenance de tableaux de bord opérationnels utilisés par des équipes internes et des partenaires externes (Power BI, Looker Studio).
- Collecte, nettoyage et consolidation de données opérationnelles multi-sources (distributeurs, opérateurs, partenaires institutionnels).
- Modélisation de données opérationnelles (flux de contenants, scénarios de coûts) dans le cadre d'un projet européen (ReUse Vanguard Project).
- Réalisation d'analyses quantitatives et de diagnostics territoriaux pour appuyer la prise de décision stratégique et opérationnelle.
- Pilotage d'études analytiques : définition des KPI, analyses de données et restitution des résultats (ADEME, Pandobac, Ecogeos).
- Contribution à la définition de référentiels de contenants standardisés avec des acteurs industriels, permettant une collecte de données homogène à l'échelle nationale.
- Coordination d'un projet européen impliquant 5 villes partenaires, incluant reporting et suivi de la performance. Outils : HubSpot, Power BI, Looker Studio
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Education
- Concepteur Développeur en Intelligence Artificielle & Analyse Big DataRNCP38616Concepteur Développeur en Intelligence Artificielle & Analyse Big Data
- Data Analytics & Analytics engineeringLe Wagon2025Full-time program focused on Analytics Engineering and the Modern Data Stack, with the design and implementation of end-to-end analytics pipelines using SQL and dbt, cloud data warehouses (BigQuery, Snowflake), and ELT ingestion via APIs and Fivetran. Advanced analytics modeling (staging → marts), data quality testing, documentation and workflow orchestration with Airflow, enabling reliable, analytics-ready datasets. Hands-on work on production-grade analytics use cases, including data ingestion from CRM and tracking tools (HubSpot, Google Tag Manager), KPI data modeling, and the development of interactive dashboards to support performance monitoring and decision-making across acquisition, marketing and sales.
Certifications
- Databricks FundamentalsDatabricks Academy2025