Isa Gafarli

• Created benchmark rates for multiple logistics activities by conducting market research, validating assumptions, and comparing sectors (Auto, Healthcare, Energy) to support strategic decision-making • Develop and maintain Power BI dashboards that visualize customer trends, sub-sector performance, and operational patterns, helping stakeholders identify efficiency gaps and new business opportunities. • Cleaned, transformed, and prepared data using SQL in Azure (Databricks/SQL environment) and connecte

• Built 10+ Power BI dashboards on a semantic/star model with reusable DAX; scheduled refresh cut manual reporting by 35%. • Designed and maintained Power BI dataflows and models for pharmacy/drugstore sell-out data, keeping KPI definitions consistent and access controlled for commercial users. • Combined cooperation/partner-pharmacy data (visibility, promo execution) with sell-out metrics to measure ROI and uplift at account/store level; surfaced best- and under-performing programs. • Agreed a standard KPI

• Extracted and modeled large credit datasets in SQL; wrote Python checks for schema/mapping accuracy, duplicates, missing values, and outliers to improve data quality for risk reporting. • Automated 5+ recurring risk reports by running Python scripts that update Tableau dashboards on a schedule, cutting manual work and reducing turnaround by 30% • Prepared model-ready datasets with clear default/cure rules for PD/LGD analysis; ran simple drift/stability checks before each model run to confirm inputs were r

• Analyzed rail freight data in R (tonnage, ton-km, revenue, on-time %, dwell/turnaround, wagon use) by corridor/route/customer; flagged delays and capacity constraints and recommended schedule, wagon, and border-handover fixes. • Built competitor intelligence (rail vs. road and neighboring operators: tariffs, transit times, lanes, service levels) and presented PPT briefings with Power BI visuals and R Markdown appendices for pricing and lane decisions. • Supported ML throughput forecasting: prepared clean

Seoul, South Korea

Statistics, Econometrics, Time Series Analysis