I currently work as a Technical Implementation Specialist on a SaaS platform dedicated to traceability and compliance.
My work sits where data, systems, and real-world constraints must genuinely fit together: understanding business processes, connecting APIs, modelling complex flows, structuring imperfect data, investigating inconsistencies, and turning sometimes unclear requirements into solutions that are usable, robust, and understandable.
An increasing part of my work involves solution design: analysing existing processes, identifying the underlying need, designing a target model, and anticipating how a decision will affect data, users, integrations, and operations. Technical documentation plays a central role in this approach. I do not see it as an addition to the product, but as infrastructure for structuring, sharing, and evolving knowledge.
I place equal importance on the human dimension: listening, explaining, helping teams with different priorities understand one another, and building bridges across professional cultures, social backgrounds, and cognitive styles.
My background is unconventional. I hold a PhD in Linguistics and worked as a palaeographer for around twelve years, alongside more conventional professional roles. I later returned to university to study mathematics before earning a French RNCP Level 7 professional qualification as an Expert in Data Science, followed by further training in RAG and agentic AI.
This combination deeply shapes the way I approach problems. Palaeography taught me how to reconstruct incomplete information from scattered clues; linguistics, how to look for structures and meaning; mathematics and data science, how to formalise relationships and test hypotheses.
For more than twenty-five years, I have developed ad hoc solutions to address concrete needs. My approach starts with the problem rather than the tool: I choose the most appropriate environment, prototype quickly, and then formalise what needs to become reliable, maintainable, and transferable.
Two phrases sum up this approach quite well:
A computer is not a typewriter with a screen.
I would hate to steal a robot’s job.
This drive towards automation has led me to work with very different environments — from VBA and Power Automate to Python, Git, and REST APIs — but always with the same objective: reducing repetitive work to leave more time for understanding, decision-making, and solving interesting problems.
I am particularly interested in AI applications that extend this approach: making documentation repositories usable as knowledge, building context-aware assistants, extracting information, validating data, and automating decisions in a controlled and purposeful way.
I have lived and worked in France, the United States, New Zealand, and Ireland. My professional experience ranges from research and teaching to industrial systems, software compliance, technical support, and SaaS implementation.
Behind this diversity, the common thread has remained remarkably consistent: understanding how a system actually works, making its structures visible, and designing tools that help people use it more effectively.
This is the direction in which I want to continue developing: towards roles in Solution Design, Technical Analysis, and the implementation of systems combining data, automation, and applied AI.