As a Data Science MS candidate at Georgia Tech with a Mechanical Engineering background from Lehigh, I blend analytical prowess with hands-on engineering experience. My journey spans from designing naval vessels to developing AI algorithms, showcasing my versatility in both physical and digital realms. With expertise in Python, machine learning, and systems engineering—honed through projects like the Sentinel ICBM—I'm driven to solve complex challenges at the intersection of AI and engineering. Holding a Secret/SAP clearance, I bring a unique perspective to sensitive, high-impact projects. My passion lies in leveraging data science to optimize systems and drive innovation, bridging the gap between traditional engineering and cutting-edge AI solutions.
My career has evolved from mechanical engineering to data science, bridging physical and digital realms. After earning my B.S. in Mechanical Engineering from Lehigh, I tackled complex projects at Northrop Grumman and Gibbs & Cox, including the Sentinel ICBM and Constellation-class frigate. These experiences ignited my passion for data, leading me to pursue a Master's in Data Science & Analytics at Georgia Tech. I now combine engineering expertise with data science, offering a unique approach to multifaceted technical challenges.
Innovation and problem-solving drive my professional identity. I excel in optimizing systems and extracting insights from data, using tools ranging from CAD software to Python and R for machine learning. My enthusiasm lies at the intersection of physical systems and data science, where I apply MBSE tools like Cameo alongside AI techniques. This holistic approach allows me to navigate both physical constraints and data-driven opportunities, creating comprehensive solutions to complex problems.
Outside work, I'm an avid outdoors enthusiast, enjoying skiing, kayaking, and mountain biking. These activities hone my real-world problem-solving skills. At home, I explore 3D printing, merging digital designs with practical applications. I'm also a passionate Philadelphia sports fan. This blend of adventure, creativity, and team spirit mirrors my work ethic: embracing challenges, innovating solutions, and collaborating effectively to achieve goals.
As a mechanical engineer transitioning into data science, I offer a unique blend of physical and digital problem-solving skills. My experience ranges from designing complex systems for naval vessels to developing AI algorithms. I leverage tools like Python, SQL, and machine learning techniques to extract insights from data, while my engineering background allows me to understand and optimize real-world systems. Whether it's creating efficient data pipelines or innovative engineering solutions, I bring a holistic approach to tackling multifaceted challenges.
My technical toolkit spans both hardware and software domains. In engineering, I'm proficient in CAD software like AutoCAD and SOLIDWORKS, with hands-on experience in 3D printing functional parts. On the software side, I excel in Python, R, and SQL for data analysis and machine learning. I'm also well-versed in systems engineering tools like Cameo and DOORS. This diverse skill set allows me to bridge the gap between physical systems and data-driven decision making, offering comprehensive technical solutions for complex projects.
With a strong foundation in systems engineering from my work on projects like the Sentinel ICBM and Constellation-class frigate, I bring a systems-thinking approach to data engineering. I specialize in decomposing complex systems, authoring technical requirements, and creating MBSE models. In the data realm, I design efficient databases, develop data processing pipelines, and implement machine learning models. My ability to see both the big picture and the intricate details makes me adept at integrating data solutions into larger system architectures, ensuring seamless functionality and performance.
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1981 S. 1300 E. Salt Lake City, UT, 84105
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