Lyon generates data. Nobody has time to use it.
Lyon is France's second-largest economy. Pharma, manufacturing, logistics, fintech, food processing. Every sector produces massive volumes of data. Clinical data at Sanofi or bioMerieux flows through validated pipelines. But the 80-person pharma subcontractor in Gerland? They export production data to CSV, paste it into Excel, and someone spends their Friday compiling the quality report by hand.
The startup scene tells a different story, but the need is the same. H7, France's largest incubator, hosts dozens of scale-ups iterating fast. They have product data, acquisition metrics, cohorts to analyze. But hiring a full-time data analyst when you just closed your Series A and don't know if the need is permanent is a risky bet.
Lyon's mid-market companies (ETIs) face a third scenario. They have a data team, sometimes a solid one. But that team is at capacity. Another dashboard project lands, a regulatory data audit comes in, nobody has the bandwidth. They need operational reinforcement, not a consultant producing a PowerPoint about data strategy.
What you need is someone who knows SQL, can clean a messy dataset, and builds dashboards connected to your sources. Available now, not after three months of hiring process.
What I do for Lyon businesses
SQL queries and ad hoc analysis
You have a business question, I have SQL and your data. "Which customer segment has the best LTV over the last 18 months?" "Why did our non-conformance rate double on line 3 this quarter?" "Which suppliers deliver late more than 10% of the time?" I find the answer in your databases, not in my assumptions. For a Lyon pharma company, that might mean cross-referencing batch data with quality control results to catch drifts. For a French Tech startup, segmenting users by behavior to identify what makes them stay (or leave). The deliverable is a clear result with commented queries.
Dashboards and automated reporting
Every Monday morning, someone on your team spends two hours compiling a report in Excel. Sometimes PowerPoint. Sometimes both. That's wasted time. I build dashboards in Looker Studio, Tableau, or Power BI connected directly to your data sources. They update themselves. At Google (through Teleperformance), I automated an entire team's reporting: 10 hours of manual work per week, gone. For a Lyon mid-market company, the gain is the same: your team stops compiling numbers and starts using them to make decisions.
Data cleaning and structuring
Your production data lives in SAP, your sales data in Salesforce, your HR data in a Google Sheet that "everyone" updates. Duplicates, inconsistent formats, empty columns, product codes that differ between systems. Before anyone can analyze anything, someone has to clean up. I take your data as-is, centralize it, standardize formats, remove duplicates, and document the structure. The result: a clean, usable dataset that your team can maintain after I'm done.
How it works
Tech stack
Frequently asked questions
Fully remote, European timezone (GMT+4, two hours ahead of Lyon). Slack, Teams, video calls, whatever tool you use. I've worked this way for years and it works better than most on-site setups. I grew up in Haute-Savoie, right next door. For kickoff or sensitive phases, I travel. But let's be honest: to build a Looker Studio dashboard or clean your data, your team at Part-Dieu doesn't need me in the office. They need the deliverable on time.
Freelance data rates in Lyon are typically 15 to 20% lower than Paris rates for equivalent quality. A dashboard connected to your sources is a few days. A full data cleanup with restructuring, one to two weeks. Longer-term team reinforcement, we set a daily rate. First call is free: we scope the need and I tell you whether it's worth the investment.
This is a classic scenario for Lyon mid-market companies. Your team is running at full capacity, another project drops in, nobody has the bandwidth. I plug into your tools, your codebase, your conventions. SQL, Python, your existing dashboards: I pick up the context and I produce. No two-week onboarding required. I've done team reinforcement for years, including at Google.
The data consultant structures your approach: audits, strategy, advanced statistical exploration (PCA, clustering, modeling). The freelance data analyst does the operational work: SQL queries, dashboards, data cleaning, team reinforcement. If you already know what you need and just need it done, you're in the right place. If you're looking for someone to explore your data and define a strategy, check out my data consulting page.
Large consultancies do great work on big transformation projects. But mobilizing Capgemini for a dashboard or three weeks of data cleaning is using a sledgehammer to crack a nut. Staffing delays, management layers, structural overhead. I'm one person, operational, available. For short, concrete projects, it's faster and cheaper.