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禁止且拒絕未經各資訊當事人同意,擅自蒐集本服務提供的使用者個人資訊資料等資料之行為。即使是公開資料,若未經許可使用爬蟲等技術裝置進行蒐集,依個人資訊保護法可能會受到刑事處分,特此告知。
© 2025 Rocketpunch, 주식회사 더블에이스, 김인기, 大韓民國首爾特別市城東區聖水一路10街 12, 12樓 1號, 04793, support@rocketpunch.com, +82 10-2710-7121
統一編號 206-87-09615
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정윤식
Data scientist with a successful track record in founding a startup and driving innovative solutions in the field of machine learning-based restaurant recommendations. Skilled in analyzing big data.
職涯
貼文
AI 職涯摘要
정윤식님은 2014년부터 데이터 분석가, 스타트업 창업자 겸 최고 데이터 과학자, 프로덕트 매니저로 활약하며 머신러닝 기반 추천 시스템 개발 및 빅데이터 분석 분야에서 전문성을 쌓아왔습니다. 특히, 개인화된 레스토랑 추천 스타트업을 성공적으로 창업하고 미국과 한국에 특허를 등록한 경험이 있습니다. 또한, CRM 솔루션 구축 및 데이터 컨설팅 경험을 바탕으로 고객 행동 분석 및 전략 수립에 강점을 가지고 있습니다.
經歷
Supply Chain Management Consulting Company at Frisco, TX. • Managed and coordinated multiple projects from initiation to completion, ensuring timely delivery and adherence to quality standards. Java-based Social Network Service web application to operate knowledge-sharing and asset-sharing platforms. • Conducted digital marketing tools like GA on web applications to analyze customer behavior and system usage. Analyzed and interpreted large data sets to identify key trends and insights to inform strategic decision-making. • Managed the entire product development process to organize designers and engineers. Contributed to developing and launching new products, collaborating with cross-functional teams to ensure successful implementation.
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Founded an innovative restaurant recommendation startup that disrupts traditional rating-based and review-focused approaches. • Taste Typology Test and Personalized Recommendations: Developed a taste typology test using structural equation modeling. Utilized the test to drive targeted marketing and personalized restaurant recommendations, resulting in improved customer engagement and satisfaction. Increased customers by an average of 7% in 36 months by inventing a restaurant recommendation system, Yummirific, based on a taste-type indicator, and performed as a web service with a computational analytics server. • Machine Learning for Customer Clustering: Implemented a machine learning model to accurately classify customer groups with similar tastes, enhancing customer experiences and increasing user retention. • Project Management and Strategic Exit: Successfully managed the project timeline for the prototype service launch in 2019 and planned the full-service launch in 2020. Strategically exited the venture due to COVID-19, leaving behind a robust foundation for future growth. • Patent Registration: Registered patents in South Korea and the U.S. can classify customers with similar taste types using an unsupervised learning algorithm and measuring users' taste-type indicators through a statistical model. • Application Development PM: Orchestrated mobile application development project, daily time usage tracking application PLANCH on the Android and iOS app store in three languages (English, Korean, Japanese), which over 5,000 users downloaded. Contracted three clients with over $20K by establishing a customized e-commerce system that can demonstrate CRM analytics report dashboard for visualizing KPIs. • Digital Marketing Management: Executed search engine marketing plans and customer experience, optimizing tools for our software and websites to increase, such as Google Analytics, Tag Manager, and Firebase.
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Prominent CRM consulting and SaaS development company based in Seoul, South Korea, serving large Korean enterprises and multinational corporations. Trusted partner delivering tailored CRM solutions for diverse industry leaders. • System Implementation PM: Developed a cutting-edge CRM Software-as-a-Service (SaaS) solution with advanced machine learning techniques and a powerful channel marketing function, enhancing CRM team efficiency and optimizing client satisfaction. • CRM Data Consulting: Provided data-driven insights and consultation on key KPIs and CRM management strategies for clients in the cosmetics, sportswear, fast food, and family restaurant industries, resulting in improved customer engagement and revenue growth. • Predictive Modeling: Analyzed customer churn, media advertising effectiveness, new product launches, and sales trends using statistical models such as time series, linear, and logistic models, enabling data-driven strategic decision-making for over 10 international clients across diverse industries. • Ad-hoc Analysis: Conducted additional reports when clients asked key questions and further strategic initiatives and analyzed key trend issues and related data to figure out the root cause, such as fraud transaction prediction for Adidas, association menu rules for Outback, cross and up-selling product analysis for Cenovis. • Reporting & Communications: Delivered periodic business analytics reports with actionable insights and data visualization to clients, facilitating data-driven decision-making at the executive level. • Business Development & Team Leadership: Established a software development business and founded the Omni-Channel Lab, a research department consisting of engineers and data scientists, resulting in a 100% increase in monetizing revenue and positioning the company as an industry leader. • Data Warehousing: Managed integrated client database architecture and pipeline, building an efficient warehouse while automating data collection from CRM campaign operations via a structured pipeline to enhance the efficiency of CRM marketing.
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學歷
• Relevant Courses: Business Analysis with Structured Data, Business Statistics, Data Management & SQL, Python for Data Analysis, Computational Data Analytics with Python, Luxury Marketing, Behavioral Economics. • Head of Learning & Development at Hult Consulting Club San Francisco. Shared significance of SQL and statistics in CRM consulting with colleagues. • Accounting Report Automation SQL programming: Developed an SQL-based accounting report automation program as a school project, providing Income Statement, Balance Sheet, and Cash Flow Statement with yearly, quarterly, and monthly options. • Stock Investment Simulator: Programed an SQL based stock portfolio simulator procedure that can perform investment report with selected period RoR, Risk, Correlation, Covariance, and Alternative stock performance. • Air France Keyword Marketing Case: Analyzed Air France’s search engine keyword marketing campaign data using R, defined six most important KPI, such as CTR, CPC, PCR, CPP, ATV and Net Income, suggested four actionable to-be model strategies. • Whole Foods Market Case: Designed structured RDBMS model through Whole Foods Market’s eCommerce system data crawling, then built a regression model to figure out “Do healthier food cost less?”, as a result, suggested three actionable insights from data analysis. • Machine Learning: Implemented regression and classification model to predict factors which can impact on revenue and cross-selling success using scikit-learn ML library, resulting in generated source code which can automatically run ML model and compare result to select the best fitted model to report. • IBM HR Case: Engineered MongoDB and Hadoop data pipeline to analyze IBM HR case, employee attrition case analysis, deployed Apache Spark on local server, created pipeline from Mongo DB to Hadoop using python, built predictive classification ML model via pyspark, at last, proposed five business insights to prevent employee attrition.
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• Relevant Courses: Statistical Social Research Method I & II. • Thesis: A Study of Measurement and Determinants of Social Capital in Local Community (2014). • Prize winner in Korea Social Science Data Archive Thesis Award. (Dec 2013). • Determined which factors of local community are affecting on building social capital in South Korea through a structural equation model using R as a master’s thesis, as a result won the Korea Social Science Data Archive Thesis Award. • Conducted Spatial Econometric Model using R to determine relationship between housing price and education environment in Seoul, as a result figure out political insights to Seoul Metropolitan Government.
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活動
最近活動
獲獎 1
專案 2
프로젝트
[보유기술] 특허 및 인증
2018년 8월 - 2021년 7월 · 3년
Registered patents in South Korea and the U.S. can classify customers with similar taste types using an unsupervised learning algorithm and measuring users' taste-type indicators through a statistical model.
프로젝트
Taste Typology & Classification Algorithm
2018년 8월 - 현재 · 7년 6개월
• Developed a predictive model using a structural equation model and K-Mean Clustering algorithm to measure users' tastes and classify groups with similar preferences, enabling personalized recommendations.
수상
한국사회과학자료원 KOSSDA 논문상
KOSSDA · 2013년 12월
정윤식, (2014), 지역사회 사회적 자본의 측정 및 형성요인에 관한 연구, 학위논문 부문 수상 https://kossda.snu.ac.kr/component/lecture/theses
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