Mason Sansom
Software Engineer
Experience
Software Engineer I
Best Buy
May 2025 — Present
Minneapolis, MN
- ▪ Develop and maintain enterprise Java applications using Spring Boot for Repair Workbench, an internal Geek Squad tool used by agents in stores and repair centers to facilitate end-user device repairs
- ▪ Build and enhance microservices-based APIs and reusable components to standardize service workflows across in-store repairs, vendor servicing, advanced repair, parts replacement, and device exchange
Associate Software Engineer
Best Buy
May 2025 — Present
Minneapolis, MN
- ▪ Engineered high-throughput data pipelines using Google Cloud Platform and Java to process customer interaction data, enabling faster decision-making and data-driven customer experiences
- ▪ Migrated data architecture to composite feature storage, reducing monthly Dataflow costs by 96% (from $1,356 to $52) and improving data accessibility for ML and analytics teams
- ▪ Migrated an existing Dataflow pipeline to a Cloud Function, reducing yearly costs from $1,300 to $4, a 99.7% reduction, while maintaining full functionality
- ▪ Took ownership of end-to-end data flow and collaborated cross-functionally with data science and analytics teams to continuously improve pipeline reliability and scalability
Associate Software Engineer Intern
Best Buy
June 2024 — Aug 2024
Minneapolis, MN
- ▪ Developed and maintained large-scale ETL pipelines using BigQuery and Google Cloud Platform, supporting critical business data workflows
- ▪ Implemented and optimized backend services with Java and Micronaut, enhancing system performance and resilience under load
Projects
Easy Going
Node.js, AWS EC2, PostgreSQL, Amazon RDS, S3
Jan 2025 — May 2025
- ▪ Designed and deployed a Node.js backend on AWS EC2 with PostgreSQL on Amazon RDS and integrated AWS S3 for secure, scalable cloud infrastructure
- ▪ Built RESTful APIs and an intelligent photo caching system, reducing redundant external API calls and improving responsiveness and cost-efficiency
CS2 Predictor
Python, scikit-learn, XGBoost, Pandas
Jan 2025 — Feb 2025
- ▪ Built an end-to-end ML pipeline that collects CS2 match data from the Liquipedia API, engineers 26 features (Elo ratings, rolling win rates, form, streaks, head-to-head records), and trains classification models to predict match outcomes
- ▪ Achieved ~65% accuracy and ~0.70 AUC with logistic regression, using chronological train/test splits to prevent data leakage and log loss for model selection across four classifiers
Education
Bachelor of Science in Computer Science
University of Utah
GPA: 3.90
Aug 2021 — May 2025
Salt Lake City, UT
Technical Skills
Languages
JavaC++PythonCC#JavaScriptNode.jsReact Native
Cloud & Tools
Google Cloud PlatformBigQueryDataflowCloud FunctionsAWSEC2RDSS3DockerGitLinuxFirebase AuthCI/CD
Databases
PostgreSQLSQL Schema Design
Activities & Leadership
University of Utah Marching Band Coding Club University E-Sports Team