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4-6 năm
6-10 năm
10-15 năm
Hơn 15 năm
Taipei, Taiwan
Technical Integration Manager @Evolution2022 ~ Hiện tại
・
Product Manager
Trong vòng một tháng
Dino Kun-Jui Lai 7+ years professional experience in customer-facing product development Skilled in cross-functional communication, scrum, problem-solving, digital ads operations, software development & project management Mobile:E-mail: [email protected] Technical Languages : C# & T-SQL Work Experience Innovation Digital, Product Manager , Apr 2024 ~ Now communication between clients and internal departments to enhance product between business and tech. Evolution, Technical Integration Manager , Apr 2022 ~ Apr 2024 communication between clients and internal departments and leading customers to integrate with software products and identify technical issues. - Build up test API server on AWS
Đã có việc làm
・
Bật trạng thái tìm việc
Full-time / Quan tâm đến làm việc từ xa
6-10 năm
國立台北科技大學 NTUT
・
資訊工程
Marketing Creative Designer, Design Lead @Cloud Gate Dance Theatre 雲門舞集2012 ~ 2020
・
UI/UX Designer
Trong vòng một tháng
Design by Soking 千綺設計 2023 FEB-JUL UX Design Intern Engaged in UX/UI projects for both business clients and government sectors, covering user research, design strategy, and UI design Coordinated UX workshops for product design education Cloud Gate Dance Theatre 雲門舞集,Chief Marketing Designer, Design Lead Coordination in multi-organization creative design projects Plan marketing strategies & campaigns for promotions UX/UI design for new production websites Key visual design Designed marketing materials and social media graphics Onion Design Associates Ltd. 洋蔥設計Creative Designer Responsible for coordinating & designing
Bật trạng thái tìm việc
Full-time / Quan tâm đến làm việc từ xa
4-6 năm
Goldsmiths, University of London
・
Creative & Cultural Entrepreneurship
Digital Marketing Manager @Amazon Web Service (AWS)2021 ~ Hiện tại
・
Digital Marketing Manager
Trong vòng một tháng
Đã có việc làm
・
Tắt trạng thái tìm việc
Full-time / Quan tâm đến làm việc từ xa
4-6 năm
輔仁大學
・
中國文學系, 新聞學系Lead Product Manager @國泰世華銀行2020 ~ Hiện tại
・
Project Manager
Trong vòng một tháng
Full-time
6-10 năm
國立政治大學
・
國際經營管理英語碩士
Ad Operator @Pixl Solutions 像素數科技術有限公司2022 ~ Hiện tại
・
Digital Marketing Manager
Trong vòng hai tháng
戶 負責規劃 B2B 產品的官網製作，以及內部產品功能改版，熟悉產品需求文件撰寫及與 PM、Engineer 的溝通方式 博丰數位 Performics / 成效行銷主任主要為客戶規劃搜尋行銷企劃，為品牌在 Google 搜尋結果建立穩定且轉換率高的獲客管道 規劃讓 新產品 Google 上有足
Đã có việc làm
Full-time / Quan tâm đến làm việc từ xa
4-6 năm
國立台灣大學
・
政治系 公共行政組
產品ＰＭ @滾石移動股份有限公司2018 ~ Hiện tại
・
行銷專員/數位行銷專員
Trong vòng một năm
[Tom] Shih-Huan Wei Have more than 4 years of Product and Project Management experience。 Passionate about learning new technology and exploring any potential possibility. Believe staying on the client-side is always the best way to do Sales,、Marketing, and Product. Business Partner Recommend Video: https://www.youtube.com/playlist?list=PLp7XBozkJirV0hHBQeARQoEGpWnxmylxb E-Commerce | Digital Marketing | Business Development & Operation | Customer Relationship Management #Google Analytics / Ads Certificate Taipei, [email protected] Work Experience (International Experience) Marketing and Promotion Staff Lycamobile Pty Ltd FebOctLeading international mobile virtual network operator
Full-time / Quan tâm đến làm việc từ xa
4-6 năm
Harvest Education Technical College
・
Business ManagementMarketing Communication & PR Manager Deputy @Le Creuset2020 ~ 2020
・
Marketing Communication & PR Manager Deputy
Hơn một năm
Full-time / Quan tâm đến làm việc từ xa
6-10 năm
Queensland University
・
MSc. Business-International Hotel MgtInternational Business Manager @IT & Service sectors2015 ~ Hiện tại
・
International Business Manager
Hơn một năm
Clement NICOLAS Proven Sales track record in APAC markets - Over 10 years living in Asia Positive, Versatile, Tech & Design lover, Digital marketing & Social media passion Taipei, Taiwan Work Experience Digital Marketing & International Business Manager • e-Commerce & Service sectors NovPresent Portfolio : 1,75 Million USD / Covered areas: USA, UK, France, Taiwan, HK, JapanSocial media & brand awareness : Blogs & Vlogs, SEO, Youtube, FB, LinkedIn... ; - Product launches planning & execution: copywriting, traffic & leads, email marketing ; - Digital marketing campaigns & strategies : paid Ads, analytics, A/B testing, optimization ; - Marketing planning, business intelligence & management, demand generation ; - Pricing and proposal generation, sales cycle management
10-15 năm
INSEEC
・
MBA International
Past
Senior Project Manager @Origin Integrated Marketing2012 ~ 2015
・
Community / Digital Marketing Manager
Hơn một năm
自然觀看數。同時，內容與官方配音募集活動做深度連結，吸引超過 1,000 組配音投稿 資深專案管理師 SENIOR PROJECT MANAGER • 純粹創意 Origin Integrated Marketing 十二月八月年 8 個月 ) 規劃執行 企業與政府單位行銷專案、擬定溝通策略、行銷活動辦理與數位內容製作 與台灣吧合作
Thất nghiệp
Full-time / Quan tâm đến làm việc từ xa
6-10 năm
NATIONAL TAIPEI UNIVERSITY OF EDUCATION
・
Bachelor of Arts
Project Manager @台灣大哥大股份有限公司 廣宣暨客戶溝通處2014 ~ 2016
・
senior marketer, assistant manager
Hơn một năm
及成績大於個人表現。 senior marketer, assistant manager Taipei Special Municipality，TW [email protected] Personal Ability Business Development 目標客群 & 市場定位分析 新客群業務開發 跨產業企業合作 Marketing 傳播策略規劃 全媒體市場溝通操作 數位社群行銷 內容行銷 Product Management 產品銷售規劃 專案預算控管 專案成效分析 Personal Highlight 獨立
Full-time / Quan tâm đến làm việc từ xa
6-10 năm
世新大學
・
Communication ManagementKế hoạch tuyển dụng đơn giản và hiệu quả nhất
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Definition of Reputation Credits
Technical Skills
Specialized knowledge and expertise within the profession (e.g. familiar with SEO and use of related tools).
Problem-Solving
Ability to identify, analyze, and prepare solutions to problems.
Adaptability
Ability to navigate unexpected situations; and keep up with shifting priorities, projects, clients, and technology.
Communication
Ability to convey information effectively and is willing to give and receive feedback.
Time Management
Ability to prioritize tasks based on importance; and have them completed within the assigned timeline.
Teamwork
Ability to work cooperatively, communicate effectively, and anticipate each other's demands, resulting in coordinated collective action.
Leadership
Ability to coach, guide, and inspire a team to achieve a shared goal or outcome effectively.
Professional Background
Tình trạng hiện tại
Đã có việc làm
Tiến trình tìm việc
Professions
Data Scientist, Machine Learning Engineer
Fields of Employment
Ngân hàng, Trí tuệ nhân tạo/ Máy học, AdTech/ MarTech
Kinh nghiệm làm việc
4-6 năm
Management
Chưa có
Kỹ năng
Ngôn ngữ
English
・
Thông thạo
Job search preferences
Vị trí
AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
Loại hình công việc
Full-time
Địa điểm
台灣台北, 台灣新北市
Làm việc từ xa
Quan tâm đến làm việc từ xa
Freelance
Đúng, tôi là một freelancer nghiệp dư.
Học vấn
Trường học
政治大學
Chuyên ngành
統計
Education
National Chenchi University, MS, Statistics, 2015 – 2017
- GPA : 3.84 / 4.0
- Master Thesis: Entropy Based Feature Selection, Professor Pei-Ting, Chou
- Objective: Build a similarity matrix based on Mutual Entropy under Hierarchical Clustering. Afterwards, select clustered features as the final selection.
- Compare the model with other feature selection methods like RF, Lasso, F-score.
National Chen-Kung University, BS, Mathematics, 2011 – 2015
Skills
Programing
- Python
- Scala
- R
- MSSQL
Data-related Tools
- Tensorflow (Keras)
- PyTorch
- Spark
- Docker
- Scikit-Learn
- Pandas
Cloud Platform
- AWS
- GCP
Language
- English: TOEFL 98 / 120
Work Experience
CTBC Bank, Model Development Department, Data Scientist
2021.12 – present
- About the department:
- Responsible for developing models related to bank recommendations and risks, including projects such as coupon recommendations, account opening marketing lists, and fraud detection.
- Job responsibilities:
- Throughout the entire project lifecycle, my primary responsibilities included model design, model training, end-to-end process development, feature design, performance tracking, and method research.
Fraud Alert Project
- Objective:
- Predicting potential fraudulent accounts based on transaction data, restricting transactions in advance to prevent harm.
- Responsibilities/Achievements:
- Development and deployment of credit card and financial features.
- Managing the data flow process from receiving variables to model predictions, identifying risk factors, and updating alert lists.
- Implemented Autoencoder + contrastive learning to achieve a 1.81% improvement in model effectiveness.
Coupon Recommendation
- Objective:
- Personalized coupon recommendations for mobile banking users to increase click-through rates and redemption rates.
- Responsibilities/Achievements:
- Utilized multi-task learning to simultaneously predict click-through behavior and coupon redemptions, resulting in a 14% increase in click-through rate and a 74% increase in redemption rate.
- Created performance tracking reports to monitor online model performance and provide insights to Business Units.
Financial Product Recommendations
- Objective:
- Tailored financial product recommendations for mobile banking users to enhance click-through rates without compromising conversion rates.
- Responsibilities/Achievements:
- Applied multi-task learning to jointly learn click-through and conversion behaviors, fine-tuned model architecture, achieving a 90% outperformance against competitor models in online testing.
Marketing List for Digital Savings Accounts
- Objective:
- Optimized conversion rates for marketing lists related to digital savings accounts
- Responsibilities/Achievements:
- successfully raising conversion rates from 0.23% to 1.16%
Work Experience
CLICKFORCE, Data Engineer Supervisor, 2020.1 – 2021.11
- About the company:
- As a top domestic digital advertisement company, CLICKFORCE cooperates with over 900 web media and over 400 mobile media to build a huge advertising environment. CLICKFORCE considers data-driven solution as the core concept of the company, and dedicates to help advertisers to achieve their commercial goals.
- At 2020, CLICKFORCE won 2 awards at Agency & Advertiser of the Year.
- Successfully acquire the exclusive advertising agency qualification for Tokyo 2020 Olympics in Taiwan.
- Job responsibilities:
- Optimize ad performance from all aspects, including the system, target audience tags, etc.
- Do researches for new ML model (recommender model, NLP model) or architecture which is suitable for our system.
- Develop data-related products or projects.
- Analyze data to help improve our system or inspect whether the demands from business side is doable.
Real-time AD Recommender System
- Objective:
- Building a real-time ad recommender system to upgrade our ad server and get better performance.
- Responsibilities:
- Figure out what kind of recommender system components that is suitable for our ad system.
- Build a tower-like and feature-cross model refer to other famous recommender system model.
- Responsible for system engineering, which includes data preprocessing, embedding generates, memory cache, cold start, model API, etc.
Interest Tags
- Objective:
- Build interest tags for ads to help ad optimizers choose their target audience.
- Responsibilities:
- Create the features from what articles they saw, what website they viewed, and what ads they interacted.
- Deal with 20 million rows data and 120 million inference samples.
- Build ML model to predict each user's behavior on certain ads.
- Using Spark through AWS EMR to accelerate the speed of producing tags.
- Achievements:
- Raise CTR performance up to 200-300% of the original tags depends on different tags, and gain more impression while maintain better performance.
- After accomplishing this project, we terminated the cost on purchasing interest tags from other company, and successfully turned the original cost into revenue by providing profitable data.
First Party Cookie Mapping
- Objective:
- Deal with the Google 3rd party Cookie issue, figure out a method to map numerous 1st party Cookies to a user.
- Responsibility:
- Transform this problem into a ML mission. Design the label of the data, figure out what feature we can get or produce and whether the feature is useful for the goal.
- Apply XGboost on this mission.
- Build a small test to prove this method works.
- Achievement:
- 70% of precision.
- One of the solution of our company while the cancelation of 3rd party Cookie happen.
Invoice Data Application
- Objective:
- Develop invoice data application.
- Responsibility:
- Responsible for fine-tuning BERT to predict category for each product.
- Produce invoice data report to brands or business unit. It demonstrates the sales volume across different channel, what kind of products are frequently bought together, and also shows comparison of target brand to the other brands.
- Achievements:
- Produce an invoice data report product.
- Produce invoice tags for ad system.
Other Experience
E.Sun AI 2020 Summer Competition, 2020.7 – 2020.8
- Objective:
- Extract names of money laundering suspects from an article.
- Responsibilities:
- Crawl the articles from different media, and parse them by using Selenium, Requests, and Beautiful Soup.
- Construct 2-step model: First, identify whether the article is related to money laundering. Second, extract the suspects' names.
- Build model serving API by Tensorflow Serving.
- Build REST API for preprocessing request data and return the prediction.
- Achievement:
- 23rd place among 409 teams.
Youtube Data-Driven Marketing System, Institute for Information Industry, 2019.8 – 2019.11
- Objectives:
- Use the title and the description of videos to automatically classify videos.
- Use the title and the description of videos to identify whether a video is sponsored.
- Give suggestions for Youtubers or companies who desire to sponsor in a video based on data analysis.
- Responsibilities:
- Apply Google API and write Python functions to get structured raw data.
- Train word vectors using Gensim based on Wiki's open data.
- Use the frequency of each sentence as a criteria to eliminate useless words.
- Tune LSTM, Conv1D, BERT on the NLP mission.
- Use EDA methods to see the insights of the data under different classes and different sponsored status.
- Achievement:
- 71% accuracy in classifying video’s type.
- 89% accuracy in detecting sponsored content.
E.Sun Real Estate Price Prediction Competition, 2019.7 – 2019.8
- Objective:
- Use the real estate training data to build a model and predict the real estate price within 10% residual.
- Responsibilities:
- Apply XGBoost, LGBM and other ML models to train the model.
- Collect the outputs as new features from each ML model and add them into the original data set to enhance the performance of the final model.
- Achievement:
- 150th place out of 1200 teams.
KKTV Data Game，2017.5 – 2017.6
- Objective:
- Predict the next video a user watch in the next time interval.
- Responsibilities:
- Extract different features from raw data, such as the latest video, the video which got the longest viewing time, the video which got the largest number of viewing.
- Use the user viewing data to construct a similarity matrix of each video as additional features.
- Achievement:
- 10th place out of 50 teams.
MRT Open Data Competition, 2017.4 – 2017.5
- Objective:
- Study the changes of passenger volume of MRT by surrounding geometric data.
- Responsibilities:
- Apply bisection method to build the edges between MRT stations.
- Combine other geometric data based on these borders.
- Use Lasso feature selection method to explore the importance of each feature.
- Add noises into features to check the features are not randomly selected.
- Achievement:
- Certificate of Honorable Mention.
Education
National Chenchi University, MS, Statistics, 2015 – 2017
- GPA : 3.84 / 4.0
- Master Thesis: Entropy Based Feature Selection, Professor Pei-Ting, Chou
- Objective: Build a similarity matrix based on Mutual Entropy under Hierarchical Clustering. Afterwards, select clustered features as the final selection.
- Compare the model with other feature selection methods like RF, Lasso, F-score.
National Chen-Kung University, BS, Mathematics, 2011 – 2015
Skills
Programing
- Python
- Scala
- R
- MSSQL
Data-related Tools
- Tensorflow (Keras)
- PyTorch
- Spark
- Docker
- Scikit-Learn
- Pandas
Cloud Platform
- AWS
- GCP
Language
- English: TOEFL 98 / 120
Work Experience
CTBC Bank, Model Development Department, Data Scientist
2021.12 – present
- About the department:
- Responsible for developing models related to bank recommendations and risks, including projects such as coupon recommendations, account opening marketing lists, and fraud detection.
- Job responsibilities:
- Throughout the entire project lifecycle, my primary responsibilities included model design, model training, end-to-end process development, feature design, performance tracking, and method research.
Fraud Alert Project
- Objective:
- Predicting potential fraudulent accounts based on transaction data, restricting transactions in advance to prevent harm.
- Responsibilities/Achievements:
- Development and deployment of credit card and financial features.
- Managing the data flow process from receiving variables to model predictions, identifying risk factors, and updating alert lists.
- Implemented Autoencoder + contrastive learning to achieve a 1.81% improvement in model effectiveness.
Coupon Recommendation
- Objective:
- Personalized coupon recommendations for mobile banking users to increase click-through rates and redemption rates.
- Responsibilities/Achievements:
- Utilized multi-task learning to simultaneously predict click-through behavior and coupon redemptions, resulting in a 14% increase in click-through rate and a 74% increase in redemption rate.
- Created performance tracking reports to monitor online model performance and provide insights to Business Units.
Financial Product Recommendations
- Objective:
- Tailored financial product recommendations for mobile banking users to enhance click-through rates without compromising conversion rates.
- Responsibilities/Achievements:
- Applied multi-task learning to jointly learn click-through and conversion behaviors, fine-tuned model architecture, achieving a 90% outperformance against competitor models in online testing.
Marketing List for Digital Savings Accounts
- Objective:
- Optimized conversion rates for marketing lists related to digital savings accounts
- Responsibilities/Achievements:
- successfully raising conversion rates from 0.23% to 1.16%
Work Experience
CLICKFORCE, Data Engineer Supervisor, 2020.1 – 2021.11
- About the company:
- As a top domestic digital advertisement company, CLICKFORCE cooperates with over 900 web media and over 400 mobile media to build a huge advertising environment. CLICKFORCE considers data-driven solution as the core concept of the company, and dedicates to help advertisers to achieve their commercial goals.
- At 2020, CLICKFORCE won 2 awards at Agency & Advertiser of the Year.
- Successfully acquire the exclusive advertising agency qualification for Tokyo 2020 Olympics in Taiwan.
- Job responsibilities:
- Optimize ad performance from all aspects, including the system, target audience tags, etc.
- Do researches for new ML model (recommender model, NLP model) or architecture which is suitable for our system.
- Develop data-related products or projects.
- Analyze data to help improve our system or inspect whether the demands from business side is doable.
Real-time AD Recommender System
- Objective:
- Building a real-time ad recommender system to upgrade our ad server and get better performance.
- Responsibilities:
- Figure out what kind of recommender system components that is suitable for our ad system.
- Build a tower-like and feature-cross model refer to other famous recommender system model.
- Responsible for system engineering, which includes data preprocessing, embedding generates, memory cache, cold start, model API, etc.
Interest Tags
- Objective:
- Build interest tags for ads to help ad optimizers choose their target audience.
- Responsibilities:
- Create the features from what articles they saw, what website they viewed, and what ads they interacted.
- Deal with 20 million rows data and 120 million inference samples.
- Build ML model to predict each user's behavior on certain ads.
- Using Spark through AWS EMR to accelerate the speed of producing tags.
- Achievements:
- Raise CTR performance up to 200-300% of the original tags depends on different tags, and gain more impression while maintain better performance.
- After accomplishing this project, we terminated the cost on purchasing interest tags from other company, and successfully turned the original cost into revenue by providing profitable data.
First Party Cookie Mapping
- Objective:
- Deal with the Google 3rd party Cookie issue, figure out a method to map numerous 1st party Cookies to a user.
- Responsibility:
- Transform this problem into a ML mission. Design the label of the data, figure out what feature we can get or produce and whether the feature is useful for the goal.
- Apply XGboost on this mission.
- Build a small test to prove this method works.
- Achievement:
- 70% of precision.
- One of the solution of our company while the cancelation of 3rd party Cookie happen.
Invoice Data Application
- Objective:
- Develop invoice data application.
- Responsibility:
- Responsible for fine-tuning BERT to predict category for each product.
- Produce invoice data report to brands or business unit. It demonstrates the sales volume across different channel, what kind of products are frequently bought together, and also shows comparison of target brand to the other brands.
- Achievements:
- Produce an invoice data report product.
- Produce invoice tags for ad system.
Other Experience
E.Sun AI 2020 Summer Competition, 2020.7 – 2020.8
- Objective:
- Extract names of money laundering suspects from an article.
- Responsibilities:
- Crawl the articles from different media, and parse them by using Selenium, Requests, and Beautiful Soup.
- Construct 2-step model: First, identify whether the article is related to money laundering. Second, extract the suspects' names.
- Build model serving API by Tensorflow Serving.
- Build REST API for preprocessing request data and return the prediction.
- Achievement:
- 23rd place among 409 teams.
Youtube Data-Driven Marketing System, Institute for Information Industry, 2019.8 – 2019.11
- Objectives:
- Use the title and the description of videos to automatically classify videos.
- Use the title and the description of videos to identify whether a video is sponsored.
- Give suggestions for Youtubers or companies who desire to sponsor in a video based on data analysis.
- Responsibilities:
- Apply Google API and write Python functions to get structured raw data.
- Train word vectors using Gensim based on Wiki's open data.
- Use the frequency of each sentence as a criteria to eliminate useless words.
- Tune LSTM, Conv1D, BERT on the NLP mission.
- Use EDA methods to see the insights of the data under different classes and different sponsored status.
- Achievement:
- 71% accuracy in classifying video’s type.
- 89% accuracy in detecting sponsored content.
E.Sun Real Estate Price Prediction Competition, 2019.7 – 2019.8
- Objective:
- Use the real estate training data to build a model and predict the real estate price within 10% residual.
- Responsibilities:
- Apply XGBoost, LGBM and other ML models to train the model.
- Collect the outputs as new features from each ML model and add them into the original data set to enhance the performance of the final model.
- Achievement:
- 150th place out of 1200 teams.
KKTV Data Game，2017.5 – 2017.6
- Objective:
- Predict the next video a user watch in the next time interval.
- Responsibilities:
- Extract different features from raw data, such as the latest video, the video which got the longest viewing time, the video which got the largest number of viewing.
- Use the user viewing data to construct a similarity matrix of each video as additional features.
- Achievement:
- 10th place out of 50 teams.
MRT Open Data Competition, 2017.4 – 2017.5
- Objective:
- Study the changes of passenger volume of MRT by surrounding geometric data.
- Responsibilities:
- Apply bisection method to build the edges between MRT stations.
- Combine other geometric data based on these borders.
- Use Lasso feature selection method to explore the importance of each feature.
- Add noises into features to check the features are not randomly selected.
- Achievement:
- Certificate of Honorable Mention.