Jin Kwon

About Jin Kwon

At Accenture, my role as a Senior Data Scientist focuses on deploying robust Trust and Safety solutions for high-impact projects like the Coca-Cola holiday campaign. With a deep understanding of AWS services and data engineering, I\'ve led the research and development of GenAI-driven moderation workflows, enhancing content safety and user experience. My expertise in deploying scalable data pipelines is augmented by a strong foundation in AWS SageMaker, AWS Glue, and Apache Airflow.The intersection of data science and marketing is where I thrive, having spearheaded Marketing Mix Models for a leading consumer goods company. I leverage these competencies to mentor budding professionals in the field, sharing insights and nurturing their growth through Udacity\'s Nanodegree programs. Our team\'s commitment to pioneering data-driven strategies fortifies our clients\' trust and positions us at the forefront of the industry.

Experience

1. Senior Data Scientist

   Accenture

   Feb 2021 — Present · Seattle, WA, US

   T&S GenAI Developer at GenAI-based Holiday Campaign | The Coca-Cola Company • Led the research, development, and deployment of Trust and Safety backend services in C# and Python, ensuring content moderation across various modalities throughout the Coca-Cola holiday marketing campaign. • Developed and refined GenAI-driven moderation workflows, optimizing prompt generation and filtering techniques to enhance content safety while maintaining seamless user experience. • Took ownership of ad-hoc tasks in C# and Python to resolve issues and maintain project flow. LLM Engineer for GenAI Code Translation | Internal LLM POC Presentation • Engineered and presented a multi-agent framework utilizing GenAI tools including Ollama, Langchain, and Autogen to semi-automate the conversion of Apache Pig scripts to PySpark (with optional human-in-the-loop). Marketing Mix Model Data Scientist | Leading Consumer Goods Company • Led the research and development of Marketing Mix Models taking responsibility for building replicable models to evaluate the performance of marketing spends across multiple channels, directly influencing budget optimization strategies. • Productionized ML models to forecast customer purchases using collaborative filtering, lifetime value (LTV) estimation, and isolation forest for anomaly detection, identifying customers most likely to purchase future marketing materials. This enabled targeted campaigns and optimized resource allocation for more effective sales decisions. Digital Marketing Insights Data Scientist | Global Media & Entertainment Company • Owned the application of clustering algorithms to identify companies likely to increase digital marketing spending, delivering actionable insights for targeted marketing strategies and supporting data-driven decision-making processes.

Education

• Rice University

  Bachelor of Science (B.S.), Chemical and Biomolecular Engineering

• Rice University

  Master's degree, Statistics

  2017 — 2019

Skills

• Python
• Bootstrap
• Apache Spark
• Data Analysis
• Jupyter Notebook
• Machine Learning
• Computer Vision
• Git
• Cascading Style Sheets (Css)
• Object-Oriented Programming (Oop)
• Sklearn
• Sql
• R
• Matlab
• Jquery
• Numerical Analysis
• Microsoft Office
• Jasmine Framework
• Html
• Hadoop
• Javascript
• Ajax
• Simulations
• Tableau
• Knockoutjs
• Cloudera Impala