Kevin Yang

Data Scientist @Rhombus Power Inc.

San Francisco, CA, US
EMAILS
k••••••••@rhombuspower.com
MOBILE NUMBERS
+16•••••••48

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WORK HISTORY

Aug 2023 — Present

Data Scientist @Rhombus Power Inc.

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Palo Alto, CA, US

Computer Vision Satellite Object Detection• Utilized Python to conduct preprocessing and data augmentation on a dataset consisting of satellite images, enhancing the dataset for model training purposes• Led the design and execution of four experiments, comparing the object detection capabilities of the YOLOv8 model and Detectron2 for defense industry clients in the context of satellite image analysis • Implemented hyperparameter tuning and curated data to significantly improve the Mean Average Precision of object detection, increasing detection accuracy from 8% to 30% for vehicles and buildings in satellite imagesPlatform Data Pipeline and API Creation• Engineered a daily data ingestion pipeline using Python and DuckDB SQL for processing flight data, achieving a reduction in processing time from 6 to 2 hours, optimizing efficiency, and lowering resource usage costs• Automated the daily data pipeline by implementing 4 Airflow Directed Acyclic Graph (DAG), streamlining the processing of 40GB of international flight data with enhanced efficiency• Deployed 4 API endpoints for clients to query news article and flight data within the company S3 storage bucket

EDUCATION

N/A

University of Toronto

Bachelor of Applied Science (B.A.Sc.), Civil Engineering

N/A

University of San Francisco

Master of Science - MS, Data Science

SKILLS

AutocadBabysittingMicrosoft OfficeCommunicationSketchupCViolinResearchCivil EngineeringTeam BuildingCommunity OutreachTeam LeadershipTime ManagementPublic OutreachTeamworkLeadershipLogistics Management

ABOUT KEVIN YANG

I am a Data Scientist working at Rhombus Power and a graduate from the University of San Francisco Master\'s of Data Science program. I am currently learning about MLOps, data engineering, and LLMS. Furthermore, I am excited about applying these technologies and concepts to solve real-world problems as a data scientist.Competencies: Python, SQL, MongoDB, Apache Spark, Apache Airflow, Apache Kafka, Google Cloud Platform (GCP), AWS, Tableau, Git, Bash, Docker

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