About Jonathan
Je conçois et déploie des systèmes de décision basés sur les données pour les équipes supply chain et opérations : modèles de prévision de la demande, logiques d'optimisation des stocks, analytique achats, reporting automatisé. Je livre des solutions opérationnelles, pas seulement des recommandations.
Depuis 8 ans, j'interviens dans l'automobile, l'aéronautique MRO, le e-commerce et le retail, sur des problématiques de planification pour des entreprises gérant entre 10 000 et 200 000 références. Mon socle technique : Python, SQL et modélisation statistique, aujourd'hui complété par un usage intensif des outils d'IA générative dans mes flux de développement et d'analyse.
Mes domaines d'intervention :
- Prévision de la demande (probabiliste, multi-horizons, demande intermittente)
- Optimisation des stocks et logiques de réapprovisionnement
- Simulation de politiques d'achat et analyse d'impact
- Cartographie des flux de données, diagnostic d'intégration, architecture de reporting
- Transformation de données ERP/transactionnelles en pipelines analytiques fiables
Parcours : 6 ans en tant que Lead Supply Chain Scientist (un rôle hybride couvrant le cadrage des besoins, la conception de solutions, le déploiement, et le suivi client) chez Lokad (plateforme SaaS d'optimisation supply chain), en charge de grands comptes (60 000 € MRR). Avant cela, R&D en science des matériaux avec un brevet publié et des publications scientifiques. Doctorat en chimie physique.
En parallèle, je développe des systèmes de génération de leads web en projets personnels avec architecture SEO, pipelines de contenu automatisés, workflows email (Astro/Next.js, Vercel, Brevo). N'hésitez pas à m'en parler si c'est pertinent pour votre projet.
Basé à Paris. Disponible en présentiel, hybride ou full remote.
Anglais natif, français conversationnel (à l'aise dans un environnement bilingue, mais interventions clients principalement en anglais).
English
Native or bilingual
French
Conversational
Can work on-site
Paris (up to 10km)
Experience
- AutoentrepreneurSupply Chain Optimization ConsultantJanuary 2024 - Today (2 years and 6 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