Gabriel Burcea

Machine Learning Consultant @Cognizant

London, GB

As a Machine Learning Consultant specializing in sales forecasting, I leveraged advanced predictive modeling techniques to forecast water sales across multiple brands, channels, and customer segments. Working within the Databricks ecosystem, I developed scalable solutions to enhance demand planning and business decision-making.Core Contributions: • Prepared and structured large-scale sales data for analysis, ensuring high data quality for forecasting models. • Developed and fine-tuned time series forecasting models, including SARIMA, Exponential Smoothing, Decision Trees, Random Forest, XGBoost, LightGBM, and deep learning approaches such as NHITS and NBeats. • Engineered feature-rich datasets to improve model accuracy and adaptability across different sales environments. • Utilized Databricks for scalable data processing and model deployment, enhancing operational efficiency. • Delivered actionable sales forecasts to stakeholders, optimizing inventory planning and revenue strategies.This role deepened my expertise in forecasting, time-series modeling, and cloud-based ML solutions, driving data-driven decision-making in the water industry.

Goldsmiths, University of London

MA Sociology, Methods in Social Research

Goldsmiths, University of London

Master of Science (MSc), Data Science

Coursera

Machine Learning and Big Data, Data Science