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上級
On
4〜6年
6〜10年
10〜15年
15年以上
Past
Engineering Manager / Technical Project Manager / Scrum Master @Kempus2023 ~ 2023
・
Scrum Master / Tech Lead / Project Manager
2ヶ月以内
Leon New Taipei City, Taiwan || [email protected] I am an experienced professional with a successful career in various fields of the IT and software industries. My prior duties include experience in Project & Product Management, Sales and Marketing, People Management, and Agile methodologies. I believe my communication and people management skills, and my past work experience will enable me to successfully integrate and flourish in any company. I have experience in the web & mobile software, networking, storage & server, ICT, and telecom industries. I am also an experienced Agile coach and Scrum Master. Work
無職
・
面接の用意ができています
フルタイム / リモートワークに興味あり
15年以上
University of Arizona
・
Mathematics
就職中
・
就職希望
フルタイム / リモートワークに興味あり
6〜10年
Fju Jen Catholic University
・
數學
Software QA Team lead @Gate.io2023 ~ 現在
・
1ヶ月以内
Bob Chen, BO-HAO,CHEN Education National Tsing Hua University ・Major : Department of Applied Mathematics After graduating, I embarked on self-study of programming languages and successfully transitioned into a software engineer. I initially delved into Linux and JavaScript, gradually gaining proficiency in Quality Assurance practices, such as test flow, Selenium, Docker, and EC2. If you're interested, please feel free to follow my GitHub profile and join me in a journey of learning from scratch. Email : [email protected] Phone :Blog : https://bobchochola.github.io/ Github: https://
就職中
・
就職希望
フルタイム / リモートワークに興味あり
4〜6年
國立清華大學 National Tsing Hua University
・
數學 mathematics,Probability,Applied Mathematic就職中
・
就職希望
フルタイム / リモートワークに興味あり
6〜10年
Vanung University
・
Industrial Management就職中
・
就職希望
フルタイム / リモートワークに興味あり
6〜10年
逢甲大學
・
Applied Mathematics
Senior Software Engineer @USUN TECHNOLOGY2019 ~ 現在
・
1ヶ月以内
FAE with industrial camera and commercial software Water and Electricity Cartographic Engineer 正暉企業有限公司 三月九月 2018 Hsinchu City, Taiwan 1. On-site supervisor. 2.Project management 3.AutoCAD (2D) hydroelectric diagram. 學歷FCU University Applied MathematicsFCU University Applied Mathematics 專案 3D-Component defect inspection machine Glass fiber defect inspection 3D-Component defect inspection machine transparent film defect inspection 2D-Component defect inspection machine Battery component defect inspection OCR inspection machine Aluminum block OCR inspection About me. As an engineer, I have gained a
就職中
・
就職希望
フルタイム / リモートワークに興味あり
4〜6年
FCU University
・
Applied Mathematics
Principal @Cascade Data Labs2016 ~ 2022
・
Director Data
2ヶ月以内
Student Assistant University of Pennsylvania Drafted and reviewed contracts to send to clinical sites Used Complio to monitor and change students' compliance status, worked with students to ensure compliance status before deadlines OctoberFebruary 2015 Assistant Researcher University of Pennsylvania Assisted with researching duties, used Lexisnexis to research and compile the activities of an international economic organization as qualitative and quantitative time series data. JuneJune 2013 Crew Member Baskin Robbins Crew member, served ice cream to patrons, and opened/closed EducationUniversity of Pennsylvania EconomicsClackamas Community College Mathematics and StatisticsGladstone High School Mathematics Key Proficiencies Delivery & Leadersh...
就職中
・
就職希望
フルタイム / リモートワークに興味あり
6〜10年
University of Pennsylvania
・
EconomicsAccountant
2ヶ月以内
selecting gold jewelry pieces, providing personalized recommendations based on their preferences and budget. Accountant • Lakshmi Ganni Traders AprJune 2022 | Eluru, Andhra Pradesh Managed financial transactions and maintained accurate records of company expenditures, receipts, and accounts payable/receivable Education Secondary School Of Education Maths, Science • JuneApril 2007 Completion of Secondary Education: ZPH High School, AprilSuccessfully completed the requirements for secondary education, including coursework in English, mathematics, science, social studies, and other subjects. Courses Computer Course Tuni, Andhra Pradesh Completed a comprehensive computer course covering topics such as computer fundamentals, operating systems, software applications, and basic troubleshooting techniques .
就職中
・
就職希望
フルタイム / リモートワークに興味なし
4〜6年
Network Engineer @Biznet (PT. Supra Primatama Nusantara)2019 ~ 現在
・
IT support engineer,network enginner,system engineer
2ヶ月以内
Shop Assistant Indomaret Group A retail company is a business entity that sells goods or services directly to consumers. EducationUniversitas Binaniaga Indonesia Information Systems Studying Information Systems involves learning about the design, implementation, and management of computer-based information systems. This field combines elements of business, technology, and management to solve organizational challenges using information technologySMAN 1 CISEENG Natural Sciences A high school specializing in natural sciences offers a curriculum focused on subjects such as physics, chemistry, biology, and mathematics. Skills Microsoft Office Network Engineering Network Security Router Configuration Mikrotik Photography Languages Indonesia - Native English - Elementary Proficiency
就職中
・
就職希望
フルタイム / リモートワークに興味あり
4〜6年
Universitas Binaniaga Indonesia
・
Sistem informasiContent Advisory Board Member @LogRocket2023 ~ 現在
・
前端工程師 Front-End Developer
3ヶ月以内
in charge of fixing mobile app made using APICloud Frontend Developer • 駿的資訊 九月九月 2019 | Taipei, Taiwan Tech used: React, GSAP, PhaserJS Responsibilities: HTML games, baccarat, lotto scratch, etc. Java Developer • appcela 六月六月 2018 | Taipei, Taiwan Tech used: Java, Struts, JSP, EmberJS Responsibilities: maintenance of ERP systems 學歷 National University of Tainan Applied Mathematics •The University of British Columbia Bsc Mathematics •did not graduate, has over 100 credits) 技能 JavaScript TypeScript React Next Tailwind CSS 語言 Chinese — 母語或雙語 English — 母語或雙語
就職中
・
就職希望
フルタイム / リモートワークに興味あり
4〜6年
National University of Tainan
・
Applied Mathematics最も簡単で効果的な採用プラン
80万枚以上の履歴書を検索して、率先して求人応募者と連絡をとって採用効率を高めましょう。何百もの企業に選ばれています。
- 検索結果をすべて閲覧
- 新しい会話を無制限に始められます
- 有料企業にのみ履歴書を公開
- ユーザーのメールアドレスと電話番号を確認
検索のコツ
1
Search a precise keyword combination
senior backend php
2
Use quotes to search for an exact phrase
"business development"
3
Use the minus sign to eliminate results containing certain words
UI designer -UX
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
現在の状況
就職中
求人検索の進捗
就職希望
Professions
Data Scientist, Machine Learning Engineer
Fields of Employment
銀行業, 人工知能／機械学習, AdTech（アドテック）・MarTech（マーテック）
職務経験
4〜6年
Management
なし
スキル
言語
English
・
流暢
Job search preferences
希望のポジション
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
求人タイプ
フルタイム
希望の勤務地
台灣台北, 台灣新北市
リモートワーク
リモートワークに興味あり
Freelance
はい、私はアマチュアのフリーランスです。
学歴
学校
政治大學
専攻
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.