Collaborated with a leading chemical manufacturing company to develop price and demand forecasting models. Utilised statistical techniques, including time series analysis, to generate accurate forecasts. Led the development of the data engineering pipeline, configured individual data flows, implemented data transformation and cleansing, developed and deployed data monitoring flows, developed and deployed forecasting model, collaborated with the dashboarding team, worked closely with the user acceptance team to ensure dashboards met needs.

Provided data-driven insights to optimize supply chain operations, reduce fill-rate risk, and maximize returns on marketing spends. Developed pipelines, dashboards, models, and a Market-mix modeling simulator using Python, R, and RShiny. Achieved a 38% reduction in daily cuts and 16% increase in incremental revenue in Mexico.

A highly motivated and proactive Decision Sciences Intern with 4 months of experience in the Pharma, CPG, Energy, and Retail industries. Carried out data analysis and developed solutions for each case study presented, utilizing various data analysis techniques and tools. Compiled a sales pitch deck for each project, which included a detailed explanation of the identified problem and proposed solutions.