Freelancer profile translated to English.
Back to original languageAbout Laura
I help tech teams transition from 'DIY' AI usage to reliable, useful, and secure assistants for their internal data.
I support companies on three concrete topics:
- Upskilling technical teams on GitHub Copilot, LLMs, and AI agents;
- Auditing the quality of RAG contexts and systems to reduce hallucinations;
- Architecting AI solutions connected to internal data, with a high level of requirement for security, governance, and traceability.
I work on real-world cases: internal documentation, code, tickets, knowledge bases, sensitive business data, internal copilots, assistants for technical or business teams.
My approach combines:
- Hands-on training, directly applicable
- Concrete audits with actionable recommendations
- Pragmatic architecture for production deployment
Topics covered:
GitHub Copilot, LLMs, RAG, context engineering, AI agents, MCP, AI governance, AI usage security, internal assistants, knowledge bases, sensitive data, local-first AI.
Formats:
- In-company training
- Team workshop
- Flash audit
- Architecture scoping
- Pilot support
English
Fluent
Spanish
Native or bilingual
French
Native or bilingual
Can work on-site
Paris (up to 50km), Bordeaux (up to 50km)
Experience
- DatalomaAI Context Engineer - Co-founderNovember 2025 - Today (9 months)
Dataloma – Context Hub | Context Intelligence App, Context Engineering (LLM / RAG / LLMOps)
🎯 Context:Creation ofDataloma, a Context Intelligence, Context Engineering appto improve the performance of generative AI (LLM) solutions by optimizing the context used for responses: documentation, knowledge base, and RAG pipelines. Approach informed by state-of-the-art research and benchmarking up to 2026, with one goal: to make context analysis measurable, actionable, and accessible.🛠 Actions Taken:- Design of a **measurable evaluation methodology applied to LLM context**: structure, redundancy, terminological consistency, readability/continuity, PII/GDPR risks, temporal consistency, with corpus + per-file analysis.- Implementation of business impact-oriented KPIs (reliability, token cost, maintainability), prioritizing high-value actions.- Integration through the creation ofMCP servers(ingestion + context provider) to connect the app to existing workflows (RAG, assistants, agents) and industrialize context analysis.- Decision-oriented visualizations (dashboards, matrices/scatter plots, drivers & recommendations) to move from diagnosis to optimization and action.- Business-first UX: results understandable by PMs/Ops/business experts, without jargon. - Pernod RicardSenior Data AnalystWINE AND SPIRITSFebruary 2023 - December 2024 (1 year and 10 months)Paris, France
Project Maestria – Consumer Journey Analysis
🎯Context:Participation as Senior Data Analyst in astrategic programto better understand consumerdrivers and barriersthroughout the purchase journey (motives, consumption moments, channels, social influence). **Deployment in key markets: India and Japan**.🛠Actions Taken:*Collection, preparation, and integrationof data from local studies- ELT data modeling inSnowflake via DBT(testing, documentation, optimization)
- Use ofGitfor versioning and technical collaboration
- Creation ofPower BI dashboardsto visualize key insights and facilitate decision-making
- Presentation and reporting of results to marketing teams and management committees
📈Results Obtained:*Successful deploymentin 2 complex markets with high potential (Japan & India)*Delivery of actionable recommendationsintegrated into Pernod Ricard's strategic plan*Time savingsof 90% in market analysis production (shift from 10 days to 1 day)🛠 Stack Used:DBT, Snowflake, Power BI, Git, SQL - Pernod RicardSenior Data AnalystWINE AND SPIRITSFebruary 2022 - January 2023 (11 months)Paris, France
Project D-Star – Multi-Market Sales Performance Management
🎯Context:Management of a team of 3 data analysts to deploy a strategic project in +5 markets (US, UK, India, China, France), in close collaboration with business, data scientists, and data engineers.Objective: Provide sales teams with reliable indicators to better prioritize their field actions.🛠Actions Taken:- Functional management of 3 analysts for the creation ofmarket-specific product impact metrics
- Development and maintenance of thedata modelin Snowflake
- Contributionto documentation, validation, and qualityof shared datasets
📈Results Obtained:- Provision ofstrategic sales indicatorsinternationally
- Delivery ofconcrete recommendationsacross +5 markets
- Measurement of the project's impact inadditional revenue for Pernod Ricard
🛠 Stack Used:Databricks, Python, Snowflake, SQL, shared documentation
Reviews
Recommendations
DO
RV
+5
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Education
- Specialized Master's Degree in Data & Marketing Analytics (Master's +6)NEOMA Business School2020- Statistiques et analyse des données - Marketing and business intelligence - CRM et expérience client - Digital Analytics - Social media analytics - Digital Analytics - Web analyse - Digital branding - Ecosystème des datas et data science - Gestion des BDD et reporting - Management des IT et du changement - Thèse professionnelle : les déterminants à l'intention d'adopter l'intelligence artificielle, le cas du livre photo personnalisé
- Higher Education Diploma in ManagementGrenoble Ecole de Management2016
Certifications
- Google Analytics Individual QualificationGoogle2021
- Data Analyst with PythonDatacamp2020
Skill set
Categories
- Other