Roman Merzifonyan

At an industrial automation distributor, I migrated a manual inventory forecasting model to SQL and Power BI, introducing SKU mapping and dynamic IQR adjustments to improve data quality. I also developed Power BI dashboards with Row-Level Security, integrating Oracle SQL to track commercial KPIs and sales performance.

I engineered Python scripts to extract supplier discount data from SAP systems into dynamic pricing models, safeguarding gross margins, and automated SO-PO workflows from purchasing documents.

Beyond my corporate experience, I am pursuing an M.S. in Statistics with research focused on B2B demand and sales forecasting using Machine Learning and Bayesian modeling. In my NYC Airbnb project, I modeled 48K+ listings using Hierarchical Bayesian Regression (MCMC with PyMC) to capture neighborhood-level variance and address heavy-tailed distributions.

Currently seeking a fully remote Data / BI / Quantitative Analytics role (CET/UK time zones) where I can leverage statistical modeling, predictive forecasting, and modern data stacks to drive commercial impact.