Freelancer profile translated to English.
Back to original languageAbout Jonathan
I design and deploy data-driven decision systems for supply chain and operations teams: demand forecasting models, inventory optimization logic, purchasing analytics, automated reporting. I deliver operational solutions, not just recommendations.
For 8 years, I have been involved in the automotive, aerospace MRO, e-commerce, and retail sectors, addressing planning issues for companies managing between 10,000 and 200,000 SKUs. My technical foundation: Python, SQL, and statistical modeling, now complemented by intensive use of generative AI tools in my development and analysis workflows.
My areas of intervention:
- Demand Forecasting (probabilistic, multi-horizon, intermittent demand)
- Inventory Optimization and Replenishment Logic
- Purchasing Policy Simulation and Impact Analysis
- Data Flow Mapping, Integration Diagnosis, Reporting Architecture
- Transforming ERP/transactional data into reliable analytical pipelines
Background: 6 years as Lead Supply Chain Scientist (a hybrid role covering needs assessment, solution design, deployment, and client monitoring) at Lokad (SaaS supply chain optimization platform), managing key accounts (€60,000 MRR). Before that, R&D in materials science with a published patent and scientific publications. PhD in Physical Chemistry.
In parallel, I develop web lead generation systems in personal projects with SEO architecture, automated content pipelines, and email workflows (Astro/Next.js, Vercel, Brevo). Feel free to discuss this with me if it's relevant to your project.
Based in Paris. Available for on-site, hybrid, or full remote work.
Native English, conversational French (comfortable in a bilingual environment, but client interactions primarily in English).
English
Native or bilingual
French
Conversational
Can work on-site
Paris (up to 10km)
Experience
- AutoentrepreneurSupply Chain Optimization ConsultantJanuary 2024 - Today (2 years and 7 months)Paris, FranceKey engagement: A US national direct-to-consumer automotive aftermarket e-commerce retailer with $250M+ revenue and ~200k SKUs (~50k purchasable).
- Built a demand forecasting solution in Python supporting demand planning and purchasing decisions with probabilistic forecasts at multiple horizons
- Designed, developed, and maintained SQL-based analytical procedures supporting inventory management and purchasing operations
- Simulated the inventory impact of proposed changes to purchasing policies, enabling data-informed decision-making at management level
- Mapped data flows and reporting requirements across departments, identifying integration opportunities and process improvements
- LokadLead Supply Chain ScientistMarch 2018 - March 2024 (6 years)Paris, FranceLokad is a supply chain planning and optimization software company, delivering end-to-end demand planning, inventory optimization, and supply chain orchestration solutions to enterprise clients worldwide.
- Owned end-to-end solution delivery and client relationships for key accounts across automotive, aerospace MRO, e-commerce, and retail, managing a portfolio totalling ~€60,000 MRR
- Scoped and designed supply chain planning solutions from initial client discovery through deployment: assessed customer challenges, quantified expected benefits, defined solution architecture, and produced proposals and documentation for scalable delivery
- Designed and implemented algorithmic inventory management and automated reordering systems integrating demand forecasting, lead-time estimation, and supplier constraints
- Ran detailed client workshops to refine scope, translate operational reality into analytical requirements, and validate solution design with technical and non-technical stakeholders
- Supported go-to-market activities by crafting solution narratives for prospective and existing clients, quantifying business benefits, and developing reusable sales and onboarding assets; mentored junior supply chain scientists on solution methodology and client engagement
- Developed expertise in supply chain planning techniques including demand forecasting, S&OP process design, inventory optimization under uncertainty, and the evaluation of advanced planning systems and tools
- SolarPrint Ltd.Research ScientistSeptember 2010 - August 2013 (2 years and 11 months)Dublin, IrelandSolarPrint was a venture-backed startup commercializing dye-sensitized solar cells, a precursor technology to modern perovskite photovoltaics.
- Designed, fabricated, and tested prototype solar cells and modules in a manufacturing R&D environment
- Co-inventor on granted patent for device optimization (WO2014090960 A1)
- Published peer-reviewed research with academic partners; identified fundamental performance limitations that directly informed the company's strategic pivot
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Education
- PhDUniversity of Liverpool2017
- BachelorTrinity College Dublin2010BA