As a Mechanical Engineer, I thrive at the intersection of engineering innovation and data-driven solutions. With over three years of experience in mechanical design, system optimization, and predictive modeling, I have cultivated a versatile skill set that bridges advanced analytics and hands-on engineering expertise.At Passion Growers, I managed the construction of a 40,000 sq-ft walk-in cooler. Leveraging Python and machine learning techniques, I developed predictive models to optimize labor allocation and forecast storage capacity, resulting in streamlined workflows and significant cost savings. My ability to integrate automation tools and design efficient systems demonstrates my commitment to driving operational excellence.During my tenure with Highlander Racing, I led the design of a 403V, 90.7 kW battery accumulator for Formula-E vehicles, using thermal simulation models and Python-based performance simulators to refine designs under dynamic conditions. I also applied finite element analysis (FEA) and GD&T principles to ensure robust and manufacturable solutions.I am passionate about leveraging cutting-edge technologies such as robotics, data visualization, and machine learning to innovate and deliver measurable outcomes. Whether it’s designing energy-efficient systems, creating machine learning classifiers, or implementing process improvements, I bring a holistic approach to solving complex challenges.Let’s connect to discuss opportunities where engineering meets data science, and where innovation drives tangible impact!