FRENCH-SPEAKING SWITZERLAND · GENEVA · VAUD · REMOTE
Freelance data analyst and AI automation specialist, serving businesses in Geneva, Lausanne and across French-speaking Switzerland (as well as France). From data collection to decision-ready dashboards, all the way to AI agents and automations truly embedded in your processes. A full-stack developer’s approach applied to data: what gets analysed also ships to production, monitored and maintained.
BASED IN MIES (VD), BETWEEN GENEVA AND LAUSANNE · REPLY WITHIN 24H
AT A GLANCE
Centralizing sources, cleaning and modelling, then surfacing it in clear, actionable dashboards. The goal is not a pretty chart, but a faster, better-informed decision.
Identifying high-volume repetitive tasks, then deploying automations and AI agents (LLM, RAG) connected to your tools. Every automation is tested, monitored and shipped, not a prototype left to gather dust.
Centralizing sources, deduplication, normalizing formats and dates, then consistency and quality checks. The result: a clean, reliable file, ready for analysis and reporting.
Remote and video-call work across Switzerland and France, and on site in Geneva by appointment, when the project requires it and as far as possible.
A first dashboard starts from CHF 9,500. Beyond that, fixed-price per project or time-and-materials at a daily rate, depending on scope. An initial scoping workshop sets the budget and priorities before any commitment.
A data analyst turns your existing data into KPIs and decisions (reporting, dashboards, analysis). A data scientist builds predictive models. Here the focus is on immediate decision value and automation, predictive models included when the need justifies it.
In Geneva, yes: on site by appointment, when the project requires it and as far as possible, for example for a scoping workshop. Elsewhere, Lausanne included, projects run remotely and by video call, across Switzerland and France.
On the data side: Power BI, Looker, SQL, Python and dbt for reporting and pipelines. On the AI side: LLMs, RAG and automation orchestrators (n8n, Make) integrated with your existing tools.
Yes. A data audit, a dashboard or an AI automation proof of concept often makes a good first milestone, before a broader engagement if the results follow.
Yes: inconsistent columns, duplicates, mixed dates and formats, empty cells, all of it is reworked and made reliable. The deliverable is a clean, documented file, along with reusable cleaning rules for your future exports.