Professional Experience

Software Engineer Intern at Raytheon BBN Technologies - 2019 (4 Months)

•Integrated external modularized systems with BBN’s codebase, and collaborated with multiple teams to debug issues.

•Set up a zookeeper to manage multiple clusters of Apache topics, measured by both systems producing and consuming events through Java to create a semantic learning model.

•Developed in a Linux based system and automated build and deployment processes of docker containers and Apache Kafka topics through bash scripts.

•Along with the development team presented the project to DARPA who funded the application.

•Participated in Agile methodologies such as Scrum, and weekly stand up meetings.

Java and C++ Tutor at Green River Community College - 2017 (6 Months)

•Promoted good code style, and documentation that enabled code readability for data structures.

•Reinforced object-oriented programming concepts taught in class to increase student’s success.

•Established a one-to-one environment with students to diagnose and debug their code.

Education

University of Washington Tacoma, GPA 3.55/4.0

•Graduated June 2020 with B.S. in Computer Science and Systems

•Annual Deans List 2019-2020

Skills

Languages: Java (Expert), Python (Intermediate), C++(Prior Experience).

Additional: Git, Apache Kafka, Docker, Linux, SQL Server, Junit testing, Scrum Methodology.

Software Projects

Meeting Scheduler - (Java, Swing, Microsoft SQL Server, Side Project).

•Aimed to learn new skillsets by using SQL, Microsoft SQL server and the benefits of databases. Learned and used JDBC framework to connect the java application to a Microsoft SQL database.

•Used interfaces and abstract classes to simplify workload, with a goal of creating readable code.

Car Brand Sentiment - (Python, TensorFlow, scikit-learn, Tweepy Twitter API, Side Project)

•Used natural language tools like scikit-learn, Vader, NLTK and TensorFlow to build a model that predicts twitter user’s sentiment’s on car brands based on twitter posts scrapped by Tweepy.

User Profiling - (Python, TensorFlow, Keras, Class Project)

•Building and using machine learning tools to create learning models that determine social media profile’s (1) age and gender, based on Facebook text update posts with an accuracy of 70 percent.

•Built Naive Bayes, K-clustering, and a multilayer perceptron to compare performances and see when to use certain models, and why each models are needed for specific classification problems.

Relevant Classes: Networking & Distribution, Algorithms, Data Structures, Databases, Computer Architecture, Quality Assurance, Machine Learning, Natural Language Processing.

Stas Katrechko

253-***-****

adhyw6@r.postjobfree.com