Location: Full Onsite. Berlin Mitte, Germany.
The company is the industrial AI operator transforming global wholesale in infrastructure, energy, and construction materials. Built on the founder’s fifth-generation trading heritage, it connects vetted suppliers across Asia, Europe, and the MENA region with local demand through a single integrated platform.
Its proprietary AI stack digitizes and automates the full lifecycle of materials trade — from procurement and pricing to inventory, logistics, and embedded financing — replacing thousands of manual, relationship-driven processes with real-time orchestration.
Buyers gain instant quotes, reliable availability, and predictable delivery through a unified operating system. Suppliers benefit from accurate forecasting, disciplined demand management, and seamless integration into cross-border fulfillment networks. The company partners with leading brands to run both dropship and cross-dock fulfillment motions for large-scale transactions, turning global supply chains into predictable, repeatable, software-like workflows.
Backed by top-tier investors and institutional financing partners, the company has scaled to triple-digit-million GMV, operates across six international markets, and is rapidly expanding toward profitability. With a team of 80+ people across Berlin (HQ) and Asia, it is building the world’s first industrial-grade AI operating system for materials — redefining how global trade works in the world’s largest and most essential industries.
You will lead and further develop the Data functions, specifically the engine that turns raw operational signals into real-time intelligence for Sales, Operations, Procurement, and Finance.
This is not a back-office analytics role, it’s a front-line leadership role. You’ll own our data models, pipelines, and metrics - and develop AI-assisted systems that anticipate what happens next: which deal closes, which lane fails, which customer churns, which supplier delays, and how all our Agentic AI performs.
You’ll partner closely with Growth, Operations, and Product to turn data into a competitive advantage - running the daily rhythm of dashboards, forecasts, and decisions that move millions in GMV each week.
Build the data backbone: Own our warehouse, models, and BI stack (SQL etc.) and ensure single-source-of-truth visibility for every team.
Operationalise insights: Work directly with Sales and Ops leadership to translate signal into action, quota pacing, margin tracking, reactivation triggers, fulfillment risks.
Develop AI-assisted workflows: Collaborate with Tech to deploy GPT-based or agentic assistants for forecasting, pricing, and anomaly detection.
Elevate reporting: Move the company from descriptive to predictive, automate recurring reports, and power daily management decisions.
Own metrics: Define, implement, and track core KPIs across GMV, NRM, automation percentage and order quality.
Coach a small team of analysts: Hire, mentor, and scale an output-driven data team that combines speed with accuracy
Bridge teams: Integrate Data into the heartbeat of the business, Sales, Ops, Finance, Procurement, and Product all run off your dashboards.
Guarantee data quality: Clean pipelines, consistent definitions, zero ambiguity.
100% alignment on KPI definitions across departments
Automated, self-updating dashboards for every business function.
Forecast accuracy >95%, margin reporting live by GMV, margin, and region.
One live AI-assisted data copilot embedded in Sales and Ops workflows within 3 months.
Significant reduction in manual reporting - ≥50% of recurring tasks automated.
Data stack clean, documented, and production-grade.
Weekly exec dashboards replacing static slide reports.
Our clients are equal-opportunity employers, and we welcome applicants from all backgrounds, regardless of race, ethnicity, gender identity or expression, sexual orientation, religion, age, disability, or any other characteristic. We believe that diversity drives innovation, creativity, and collective strength.
#J-18808-LjbffrTyp:
VollzeitArbeitsmodell:
Vor OrtKategorie:
Erfahrung:
2+ yearsArbeitsverhältnis:
AngestelltVeröffentlichungsdatum:
29 Nov 2025Standort:
Berlin
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