Born and raised in Seattle, diehard Seattle sports fan, but living in Boston, Massachusetts.
I have a passion for football, motorsport, cooking, history, and gaming, so just a big hodgepodge of interests.
While a Systems Engineer, I have an extensive technical background. I have had a love for technology and computers since a young age. I built my first computer when I was 13, started learning (unsuccessfully at the time) coding at 15, then life led me to attend the University of Michigan. I intended to get a degree in Computer Science and a minor in Statistics, but I found a degree in Data Science that merged the two.
I had the fantastic opportunity to work at a small startup where I got the chance to interact with customers on a near-daily basis. That time allowed me to discover a passion for developing relationships with people and helping them solve problems. I love the process of designing, implementing, and iterating upon solutions to help solve multidimensional business problems and generate value for clients. It excites me since no two clients will have the same issue; therefore, no solutions will be the same.
If I sound like somebody that your company could use, feel free to reach me at my email here!
I work on the Qatar Air Defense Operations Center (ADOC) program as Qatar prepares for the upcoming 2022 FIFA World Cup. I joined the program just as the U.S. Air Force awarded Raytheon with the responsibility to integrate the National Advanced Surface-to-Air Missile System (NASAMS) into the ADOC.
My responsibility was to design, implement, and maintain new features and enhancements of legacy features due to NASAMS integration. One such task was expanding our Threat Evaluation and Weapon Assignment (TEWA) algorithm for the new weapon platform. When designing new features, I had to build relationships with project stakeholders and program management, convincing them that the new features I had designed met the customers' stringent performance and operability requirements. I would then implement the solutions that I had designed. Our team had a strong Summer of 2021, and we were able to deliver our new features 2 months ahead of schedule.
While our teams began the transition into a maintenance cycle, I had the opportunity to lead a small team of junior engineers with the sole focus of preparing our software for new-customer demonstrations. We worked closely with our Business Development counterparts to iterate upon our software to highlight our value-based differentiators during demos. I would drive our software during these demos, occasionally answering technical or operational questions from high-ranking military officials. My team also developed materials compliant with Department of Defense export-control regulations for the generals to take back to their countries for further inspection.
We expect contracts resulting from these demos to be worth over 10 billion USD.
Achievements:
4x Formal Awards from Project Leadership for Software Development.
Formal Award from Program Leadership for Demo work.
Promoted to Systems Engineer II in April 2022
A small startup company in Michigan created an esports marking tool that tracks, measures, and monitors crucial information for both organizations and brands. Twitch sees an average of 15 million daily active users, so we wanted to create a platform that would allow brands to maximize the return on streaming sponsorships.
I created a program that would scrape Twitch chat and a streamer's live-stream audio to create audience profiles. These profiles would combine Twitch chat sentiment, brand interactions, demographic data, and more.
I then designed and implemented a commercial service using our audience profiles to recommend specific influencers to companies based on understanding the brand and the audience they wanted to reach.
At Medion, I worked with the Product Management team to oversee the launch of a new education ultrabook in Switzerland and conducted gap analysis for virtual assistant integration in smart displays.
My primary responsibilities at Medion were overseeing our product release schedule was on track for the start of Back To School shopping. I was able to help cut our costs by 8% by sourcing accessories from a different supplier that met our specs. This allowed us to keep on our original release schedule while increasing our profits. In addition, I did extensive quality assurance on the sample products that would arrive daily from our suppliers, creating presentable materials and tracking defects for our team and leadership to review.
I also conducted a gap analysis for virtual assistant integration in smart displays. Leadership desired to understand the differences between each available option before choosing a virtual assistant. I presented my findings to the CTO, but just a few days later, he got a directive from the parent company announcing an exclusive smart assistant deal with Google.
At Razer, I was able to bring my passion for gaming and passion for sports together.
I researched our customer profiles and found gaps in our customer demographics that we could capitalize on.
With the emergence of NFL stars like JuJu Smith-Schuster, who had large social media followings but were also avid gamers, I proposed to marketing leadership that seeding products to influences like them would break the mold that gaming is just for "nerds."
I reached out to WWE's Austin "Xavier Woods" Watson, NBA's Gordon Hayward, NFL's JuJu Smith-Schuster and Eric Berry, amongst others, to gauge interest in becoming partners with Razer. I left before negotiations were concluded but was later informed that they had signed three influencers on my shortlist to exclusive sponsorships.
While waiting for email responses, I also helped organize a social media campaign during ESL Cologne 2017, created a promotional tournament format that is still being used today, participated in product development and testing, and created internal training materials.
Graduated with a Bachelors in Data Science. GPA: 3.62
The Data Science program at the University of Michigan was a joint program between the EECS (Electrical Engineering and Computer Science) Department and the Department of Statistics. It is a rigorous program that provided me with the foundation in aspects of computer science, statistics, and mathematics relevant for analyzing and manipulating large complex datasets and teaching the theoretical properties underpinning the performance of the algorithms and methods.
I was also a member of the University of Michigan's Overwatch team and Captain for three years. Overwatch is a 6 vs. 6 team-based multiplayer first-person shooter game, and we played on the competitive collegiate ladder. We placed second in our region in 2018 and 2019 but could not get to the National Invitational tournament. As team captain, my responsibilities included running team reviews, creating new strategies, and roster and player management.
Relevant Coursework:
DATASCI 485 - Capstone
DATASCI 415 - Data Mining and Statistical Learning
STATS 413 - Applied Regression Analysis
STATS 412 - Introduction to Probability & Statistics
EECS 485 - Web Systems
EECS 484 - Database Management Systems
EECS 442 - Computer Vision
EECS 388 - Introduction to Computer Security
EECS 370 - Introduction to Computer Organization
EECS 281 - Introduction to Data Structures and Algorithms
EECS 280 - Introduction to Programming
POLSCI 490 - Game Theory
SI 422 - Needs Assessment and Usability Evaluation
IOE 310 - Optimization and Computational Methods
IOE 202 - Operations Engineering & Analytics
MATH 215 - Multivariable & Vector Calculus
MATH 214 - Applied Linear Algebra
Achievements:
Deans List
University Honors
Used player data from PFF and Pro Football Reference to train a supervised machine learning model to predict player fantasy performance.
Model variables included, but were not limited to:
A player's historical statistics, weighted to favor most recent seasons played and incorporated Strength-of-Schedule, coaching staff and coaching staff experience, PFF performance grades for Offensive Linemen, NFL player comparisons for rookie players...
Placements:
2020 - 2nd Place
2021 - 1st Place
Spent a day building supervised machine learning, analyzing socioeconomic factors, industrial water usage to predict drought severity across counties within the United States.
Our team of 4 software engineers cleaned, explored, visualized, and analyzed Big Data to create and refine our ML models to develop recommendations for county governments for drought mitigation.
Created visualizations using Tableau and machine learning models using Python.
Selected to be the only under-graduate finalist and presented in front of an expert panel of judges from E&Y, Llamasoft, Deloitte, PWC, Cummins, Stryker, Correlation-One, the Paton Center, and faculty