Experience
A journey through building products and leading engineering teams
Founding CTO
Moriah
November 2025 - Present
Paris, France
Leading Moriah's strategic pivot to become a fully AI-native digital marketing powerhouse. Driving ROI-focused technology initiatives across all operations.
- Leading strategic pivot to AI-native digital marketing
- Building ROI-driven technology solutions
Senior Data/AI Engineer
MadKudu
November 2024 - November 2025
Mountain View, CA
Contributed to the company's shift toward an AI-native architecture by helping design internal AI processes and developing components of the MCP server.
- AI-Native Transformation & MCP Server Development: Designed internal AI processes and developed MCP server components for smoother AI agent integration
- AI-Ready API & Data Infrastructure: Designed and exposed internal Data API with AI-first approach for automated agents and cross-functional teams
- Advanced ETL Engineering: Built and optimized large-scale ETL pipelines for high reliability and performance
- Feature Ownership & Delivery: Led development and deployment of ambitious product features
Tech Lead / Senior Data Engineer
L'Oréal
July 2023 - August 2024
Clichy, France
Led the Data Engineering team, overseeing project planning, resource allocation, and timely delivery of data initiatives.
- Technical Leadership & Management: Led Data Engineering team, overseeing project planning and resource allocation
- Data Pipeline & ETL Development: Designed and maintained robust ETL pipelines for high-volume data
- Back-End Development: Built and managed Back-End APIs for seamless downstream integration
- Data Warehouse Management: Oversaw design, optimization, and administration ensuring data integrity and performance
- Cloud Infrastructure: Managed multi-cloud environment (GCP & AWS) for scalability and reliability
Late Founder & CTO
Nalia
January 2020 - June 2023
Paris, France
Pioneered the development and launch of a B2B SaaS solution for Customer Success teams, enabling proactive portfolio management through data-driven task prioritization and Customer Churn Prediction.
- Technology & Strategy Leadership: Directed entire technological roadmap and architecture, translating complex business needs into a scalable product
- Team & Project Management: Led and managed technical team, overseeing sprint planning and successful feature delivery
- Architecture Design: Designed robust Back-end Architectures and optimized Data Models for high-volume, real-time customer success data
- Automated ML Implementation: Integrated Customer Churn Prediction and predictive scoring for task prioritization
- Business Acumen: Served as critical bridge between technology and business strategy
Teacher
ESME-Sudria
December 2020 - June 2021
Paris, France
Designed and delivered a core curriculum module on Applied Statistics for Machine Learning to final-year Engineering Master's students.
- Designed and delivered curriculum on Applied Statistics for Machine Learning to Master's students
- Mentored high-potential students, transitioning theoretical knowledge into practical AI/ML skills
- Validated deep expertise in statistical methodologies (hypothesis testing, regression, probability theory)
Technical Writer
Towards Data Science
May 2020 - February 2021
Remote
Contributing Author on the largest data science publication, authoring technical articles on cutting-edge topics in Data Science and Data Engineering.
- Authored and published technical articles on Data Science and Data Engineering for a global audience
- Translated complex technical concepts into clear, engaging, and actionable content
Data Scientist
Société Générale
May 2019 - October 2019
Fontenay-sous-Bois, France
Developed and deployed an Unsupervised Predictive Maintenance (UPM) solution to proactively anticipate server failures using high-volume log stream data.
- Developed UPM solution to proactively anticipate server failures using high-volume log stream data
- Leveraged Deep Learning (Autoencoders) for sophisticated anomaly detection
- Implemented LSTM models for accurate time-series forecasting of server health and resource usage