Belmont, California, United States
I leverage my expertise in analytics to optimize supply chain processes and drive business growth. With over 6 years of experience in the field, I have successfully led system integration and automation projects, created executive-level dashboards, and developed data pipelines and new supply chain models. I am passionate about using data to inform decision-making and improve operational efficiency. I have a Master of Science in Analytics from Georgia Institute of Technology and an Operations Management Certificate from Caltech. I also hold a Data Engineer Associate and SQL Server Developer Career Track certifications from DataCamp. I am always eager to learn new technologies and methodologies to enhance my performance and contribute to the success of my team and organization.
In my role as an Engineering Program Manager and Data Scientist at HP in Palo Alto, California, I successfully led the integration of Poly's Maquila into HP standards for the Mexican Import/Export Customs team. Additionally, I oversaw the product relabeling schedule for Poly's transition to HP SKUs and gathered business and IT needs for redefining inventory target weeks of supply. I specialized in creating reports and dashboards using Power BI, including managing the data pipelines, designing the data models in the back end, and providing a smooth stakeholder experience.
• Led system integration and automation projects to reduce manual work hours for Order Management and Customs teams at Poly. • Gathered business and IT requirements to streamline processes and increase efficiency. • Helped hire and train Poly's analytics Center of Excellence for supply chain improvement. • Created executive level dashboards reflecting the current state of the company's supply chain on one, exportable page.
Led the development and implementation of new supply chain models and data pipelines at Poly, resulting in optimized processes and data-driven decisions. • Collaborated with cross-functional teams to design and implement supply chain models. • Analyzed quarter end revenue, shipment performance, and inventory levels for insights. • Implemented data pipelines and dashboards for decision-making.