Experience level:
3-5 years
Education level:
Bachelor
Languages:
Russian: Native
English: B2
Serbian: A1
Logistics specialist, business and data analyst with 5 years of experience in transportation logistics, digital transformation, and financial modeling. Currently seeking opportunities as a data analyst to apply analytical thinking, business insights, and SQL skills to real-world challenges.
From 2021 to 2024, I worked on a large-scale logistics digitalization project for SIBUR, one of the leading petrochemical companies in Russia. My role included process design, implementation of logistics solutions, and adapting workflows amid external disruptions. I focused on using data to optimize supply chain performance.
In 2024, I developed 10+ financial models for a consulting firm supporting franchise launches in HoReCa, automotive services, and education. My work involved building calculation logic, analyzing results, and presenting actionable recommendations. I regularly use SQL, Excel, Google Sheets, and data visualization tools in my work.
Open to full-time or project-based remote opportunities, with compensation in either rubles or foreign currency. Interested in roles at the intersection of logistics, analytics, and consulting, especially where data-driven thinking and systematic problem solving are valued.
Participated in the launch and implementation of a digitalization project for road logistics. Developed a system for tracking export shipments to European partners using a “short-haul” (last mile) approach. Monitored OTIF (On Time In Full) performance metrics and oversaw the quality of service provided by 30+ transportation contractors.
Led a project on the digitalization of road logistics for petrochemical products (granules, films, bulk chemicals) for SIBUR. Responsibilities included cargo tracking, data analysis, communication with Russian and European partners, and overall project optimization.
Key Results:
Designed and improved a cargo tracking system covering all stages from vehicle arrival at the loading site to final unloading.
Implemented a reporting and analytics framework to monitor carrier performance (tracked over 2,500 vehicles per month), including data collection and service quality assessment.
Optimized the supply chain by reducing lead times and selecting the most reliable logistics partners based on performance analytics.
Successfully addressed a key business challenge: improving service quality through on-time delivery, proactive customer notifications about potential delays, and real-time rerouting during unforeseen events (e.g., changing international border regulations).
The project significantly reduced delivery disruption risks and enhanced the company’s reputation among clients and partners.
Technical Skills:
Microsoft Excel (Advanced): Proficient in data processing, automation with macros, and Power Query for ETL tasks.
Data Visualization: Experience creating dashboards and visual reports using Tableau.
Statistical Analysis: Applied basic statistical methods for data interpretation, forecasting, and optimization in logistics and operations.
SQL (Basic): Able to write simple queries for data extraction and transformation from relational databases.
Data Analytics Tools: Familiar with SPSS for exploratory and descriptive data analysis.
Inventory and Operations Modeling: Knowledge of inventory control models (e.g., ABC analysis, EOQ), cost optimization techniques, and pricing models for warehouse and transport services.
Domain Knowledge: Understanding of WMS (Warehouse Management Systems), TMS (Transportation Management Systems), and international trade frameworks (e.g., Incoterms).
Soft Skills:
Analytical Thinking: Experienced in diagnosing inefficiencies in logistics and financial systems; skilled in identifying hidden patterns and proposing data-driven solutions.
Data-Driven Decision Making: Comfortable working with large datasets, ensuring precision in analysis, reporting, and interpretation.
Adaptability & Flexibility: Proven ability to adjust quickly to changing project requirements and external constraints; skilled at spotting non-obvious insights in data.
Presentation & Communication: Capable of clearly articulating analysis results and formulating actionable recommendations backed by data for both technical and non-technical stakeholders.