Freelancer profile translated to English.
Back to original languageAbout Alexandra
I help companies structure, model, and leverage their data to make better decisions, faster.
I build robust ELT pipelines, maintainable analytical models withdbt**, and relevant dashboards with BI ( **Tableau / Power BI / Looker).
👉 Services offered:
• Data Architecture &modern data stack
• Modeling and testing with dbt
• Data integration and ingestion (APIs, pipelines)
• Exploratory analysis & business KPI definition
• Visualization & operational insights
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)
- Definition, structuring, and monitoring of 20+ operational KPIs (volumes, return rates, logistics costs, performance).
- Design and maintenance of operational dashboards used by internal teams and external partners (Power BI, Looker Studio).
- Collection, cleaning, and consolidation of multi-source operational data (distributors, operators, institutional partners).
- Modeling of operational data (container flows, cost scenarios) within the framework of a European project (ReUse Vanguard Project).
- Conducting quantitative analyses and territorial diagnostics to support strategic and operational decision-making.
- Management of analytical studies: KPI definition, data analysis, and results reporting (ADEME, Pandobac, Ecogeos).
- Contribution to the definition of standardized container repositories with industrial stakeholders, enabling homogeneous data collection at the national level.
- Coordination of a European project involving 5 partner cities, including reporting and performance monitoring. Tools: HubSpot, Power BI, Looker Studio
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Education
- Designer Developer in Artificial Intelligence & Big Data AnalysisRNCP38616Concepteur 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