Brevin Simon

I have a deep enthusiasm for the field of Data Engineering and Machine Learning and an eagerness to join a position where I can gain professional experience. My career aspirations transcend monetary gain; I am driven by the pursuit of invaluable work experience and the opportunity to learn alongside a talented team. During my senior project at Microsoft, I was immersed in the world of data transformation and unsupervised learning, where I collaborated closely with Microsoft Data Engineers on their Azure user telemetry data. The experience ignited my passion for leveraging data to drive innovation and inspired me to continue pursuing a career in the domain of data science.

Taking a gap year post-graduation, I delved into Amazon Web Services, broadening my skill set beyond the conventional scope of my degree. Although cloud services were absent from my coursework, my dedication led to the attainment of AWS Solutions Architect Associate and Machine Learning Specialist certifications. I acquired a fundamental understanding of the cloud, along with a rich vocabulary of industry-specific terminology. Continuing my journey, I've continued to use different AWS services and frameworks with Terraform, enhancing my ability to learn and deploy these solutions. I am excited to explore opportunities in Data Engineering and Machine Learning that align with my passion for learning and growth. Please feel free to reach out to me through my social media channels on the toolbar of my site. Thank you for considering my application where-ever you may be.

Over the past year, I decided to learn about Cloud Computing since it was never touched in through school and I found it to be very important in the scope of engineering technology. After working with Microsoft Azure and seeing what their cloud solutions had to offer, I was motivated to learn about what the cloud had to offer. Through personal research I decided to focus in on Amazon Web Services (AWS) since I felt they had better documentation and would make the journey of learning in-depth cloud computing architectures less difficult.

I began learning simple ways to host my personal website but later felt motivated to study for a certification to help expand my knowledge of their cloud more quickly. Given my degree in Computer Science I decided to dive straight into the Solutions Architect Associate exam and throughout the journey I learned complex topics that I had never been able to learn in the University environment. These topics include networking, routing, edge devices, the OSI model, load balancing, scaling virtual machines, different managed databases, and much more. Bringing all these topics together were akin to my current skill set and helped reinforce the knowledge I garnered throughout my schooling at Washington State University.

Before studying for the Solutions Architect exam, I had done research into the Machine Learning Specialty and knew it would be unachievable with my little knowledge of the AWS cloud. Toward the end of my studying for the exam I pre-emptively indulged into the Machine Learning AWS book and started working with SageMaker as I felt it was being hidden from me during my studying. My experience in the Computer Science field has always been data science, and machine learning oriented so learning this service was a great change of pace from studying for solutions architecture.

Having the ability to add SageMaker to my skillset, connecting the service with the world of AWS architecture and my machine learning knowledge from university felt as though it was all coming together. As of August 23, 2023, I have just recently passed the Machine Learning Specialty exam and I am now motivated to implement more solutions in the cloud to get more hands-on experience as I feel it is keen to being successful in this field. Through this I would also like to teach myself to be more fluent in Java, JavaScript, and Scala so I can broaden my range of expertise.