Juhong Park

Experience

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  Onnetsystems Korea

  Jan 2012 - Apr 2013

  Software Engineer, Streaming Team

  • Developed automation program for this streaming solution co., serving leading telcos, reducing engineers' work time by 90%.

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  Devsisters

  May 2013 - Aug 2019

  • Initiated and led a data science group that defined a data analysis framework and implemented it to maximize company profit. Participated in the C-levels' decision-making process about business planning and solved their problems by data analysis. Defined a data analysis framework to analyze user behavior for each business portfolio and implemented it in the games of the company and its subsidiaries.• Improved return on performance marketing investment by 11% via optimizing marketing channel mix based on customer lifetime value. Selected profitable channels by predicting future revenue paid by customers from each channel in their lifetime. The marketing strategy was presented at NDC (Top industry conference) and reported as a notable session by the press.• Increased customer retention rate by 7% through improving customer experience based on customer behavior analysis. Found customer pain points (ex. unfavorable user matching system, item reward dissatisfaction) by decision tree analysis and planned response strategies with a product manager. Added related KPIs to track the constant changes in customer needs. Show less • Initiated and led a data division that built a data processing system and conducted business performance analysis. Introduced data governance and facilitated data analysis and utilization within the company.• Reduced data analysis time and cost by 80% by designing a data analysis system based on serverless frameworks on AWS. Maximized analysis efficiency by eliminating unnecessary server execution and wait time. The system architecture was recognized as a best practice by AWS and presented at Gaming on AWS. Enhanced enterprise-wide data utilization by 40% by creating a real-time dashboard by which managers can analyze data. Provided regular training on analysis using the dashboard to strengthen managers’ analytic abilities.• Expanded the data processing capacity over 200 times by applying a distributed big data framework while cutting cost per server by 70% through utilizing reserved servers and short-term servers on AWS.• Designed a data log structure and KPIs of a new product by Interviewing the product manager to identify the important parts for customers and testing the product to make the log structure efficient. Created a dashboard to show the status of the product immediately after its launch. Show less • Joined early stage (about 10 employees) and contributed to the growth (YoY 8,500% in 2015) and going public ($1 billion valuation).• Released and managed a new mobile game played by 10 million daily active users worldwide. Launched a cloud server system to handle massive user traffic and established a server operation strategy for responding to traffic fluctuation and system failure. The operation strategy was presented at the LINE conference as a best practice.• Founded the KAIST Branch for researching and networking at KAIST. Led a joint study on customer behavior with KAIST and organized mobile technology seminars every six months. Show less

  • Data Scientist / Group Leader, Data Science Group

    Jan 2019 - Aug 2019

  • Data Scientist & Data Engineer / Team Leader, Data Science & Infrastructure Team

    Jul 2016 - Dec 2018

  • Software Engineer, Server Team

    May 2013 - Jun 2016
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  Biostatistics & Bioinformatics Laboratory

  Sept 2019 - Aug 2021

  Graduate Researcher

  • Employed the Deep Autoencoder methodology to extract predictive latent variables from extensive genome data, enabling the creation of an outbreak prediction model for Diabetes development and leading to a significant enhancement in the predictive performance index (AUC) compared to the previously utilized Polygenic Risk Score methodology.• Applied NLP methodology to Discharge Note and formulated a Deep Learning model for predicting the probability of readmission in discharged patients based on extracted key information, resulting in an impressive AUC of 80%.• Implemented Explainable AI techniques to facilitate doctors' active utilization of the AI model, leading to significant advancements in the new AI system’s usability.• Utilized Machine Learning and Deep Learning techniques to analyze diseases such as diabetes, Covid-19, COPD, mental illness, and dementia using genomes, patient medical records, cohort data, multi-omics, MRI images, and more, ultimately predicting their occurrence and developing biomarkers and prediction models. Show less

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  Boston Consulting Group (BCG)

  Oct 2021 - Sept 2023

  Consultant

  • Proposed management strategies for leading global companies across sectors such as digital platforms, private equity, financial institutions, banks, insurance, EPC, and more. Focused on formulating digital transformation strategies, facilitating the effective implementation of data and AI technologies, and establishing agile organizational structures.