Galvanize's Data Science Immersive provided me with advanced knowledge in statistics, machine learning algorithms, and data engineering. Over the course of 12 weeks, I applied these skills using industry standard tools to evaluate various real world datasets.• Used machine learning to build both descriptive and predictive models• Completed case studies and defended analysis by presentation among peers• Scraped large data sets from several websites such as NYTimes, Yelp, F1

• Managed initial technical design, schedule, and budget of smart lamp products • Designed and simulated thermal performance of actively cooled elements • Validated simulation results with measured data from in-house lab tests• Managed cross functional design efforts with electrical team to insure proper electrical, mechanical, and optical features were incorporated into prototype and production PCBAs• Gathered and evaluated feedback from key stakeholders, including customers, during lamp development and managed expectations of final deliverables• Collaborated with industrial design contractor to repackage lamp products using visual elements to unify product families and strengthen branding• Facilitated new product introduction with domestic and international manufacturing partners • Hand-built and tested prototypes using various rapid prototyping and machining methods

• Designed mechanical packaging for first product to reach volume production• Evaluated data in MatLab to validate thermal performance of new designs• Defined KPIs to collect and analyze to improve manufacturing quality• Implemented MRP system to streamline engineering operations

• Automated product assembly for electronic security startup, increasing daily throughput• Streamlined electric motorcycle battery assembly for cost effective domestic production