Iuliia Kozina

Senior Logistics Consultant Data-driven Decision Making, Scenario Development @DB Engineering & Consulting

Berlin, DE
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WORK HISTORY

Jun 2023 — Present

Senior Logistics Consultant Data-driven Decision Making, Scenario Development @DB Engineering & Consulting

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Designed the demand architecture and logistics service concept for a large-scale urban development (600k residents), reducing projected transportation load by 20% and improving forecasting accuracy by 18%- Scoped phased logistics service delivery across 170+ sites and aligned 15+ stakeholders on capacity assumptions, risk boundaries, and implementation sequencing- Developed scenario-based demand models through 2030 by informing infrastructure planning and CAPEX decisions.

EDUCATION

2001 — 2007

Saint Petersburg State Institute of Technology (Technical University)

Engineer's degree, Biotechnology

N/A

Saint Petersburg State University of Aerospace and Instrumentation

Master's Degree, Innovations and Technologies

N/A

INSEAD

AI Founder 2025 Sprint

N/A

Higher School of Economics

Master's degree, Computational and Applied Mathematics

2019 — 2021

NUS Business School

Master of Business Administration - MBA, Business Administration, Management and Operations

ABOUT IULIIA KOZINA

I work at the intersection of business strategy, operations, and data, helping transport, logistics, and infrastructure organisations turn complex operational problems into scalable data-driven solutions. For 15+ years, I’ve been designing and orchestrating strategic, analytical, and transformation initiatives across Europe, Central Asia, and Southeast Asia. My work consistently focuses on one thing: aligning business logic, data, and operational processes so companies can operate faster, more efficiently, and with fewer costly mistakes. I’ve delivered more than €500M in measurable business impact, leading initiatives in demand forecasting, operational optimisation, predictive maintenance modelling, and logistics strategy. Recent results include:• +20% forecasting accuracy• –20% projected logistics load enabling CAPEX deferral• –30% infrastructure maintenance costs• –15% operational spend• +20% freight volume uplift with –10% churnMy strength lies in seeing the whole architecture of a problem: operational flows, data dependencies, regulatory constraints, and business logic and converging them into solutions that create long-term and scalable value: i••••••••@u.nus.edu :@JuliaKozina

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Iuliia Kozina — Senior Logistics Consultant Data-driven Decision Making, Scenario Development at DB Engineering & Consulting in Berlin, DE | Unifers