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後端工程師 @Canner (易開科技)
2023 ~ 2024
Senior Backend Engineer
Within one month
產品數據中台,專注於新功能開發、問題排查,並致力於優化團隊的開發流程。參與公司開源專案 accio 的 DSL parser 開發,負責開發 ChatGPT 自然語言獲取數據的 Plugin。 #Node.js #Typescript #Data Modeling #GraphQL 後端工程師 愛酷智能科技 AccuHit AI technology company 九月三月 2023 Taipei, Taiwan 主導團隊升級 PHP
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東海大學 Tunghai University
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高級工程師 @電商
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軟體工程師、影像處理工程師、AI處理工程師、演算法工程師
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系統架構 。 重構 TensorFlow Model Server AI 專案,實作 gRPC 協定減少通訊延遲 。 使用 PySpark 和 Apache Beam 處理深度學習的億級資料前處理 。 利用 Spring Boot 改進了 NLP 專案,增加模組化設計、新增單元測試,加入微服務同步機制 。 獨力建置 ELK Satck Cluster with Basic Security 基礎建設,使用 monitoring with metricbeat 和 beats 蒐集資料
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國立台灣科技大學
資訊與通訊
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系統軟體開發工程師 @繽紛科技股份有限公司
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解鎖頁面畫面及邏輯 -使用git及linux語法(系統)進行版本控制及Android OS Image file建構 Aristotle Smart Home Devices -babytracking's intent reaction design by javascript -相繼與IBM及PullString合作NLU自然語言辨識STT、TTS相關訓練 -解析語音辨識回傳結果JSON格式之intent及entity -協助其他功能除錯 -使用Node.js安裝系統 工程師
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軟體工程師/品牌開發專員 @冠淳科技股份有限公司
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Senior Backend Engineer @iKala 愛卡拉互動媒體股份有限公司
2023 ~ 2024
Data engineer / Backend engineer / Software engineer
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Python
GCP
Algorithms
Unemployed
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6-10 years
國立成功大學
資訊工程
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Avatar of 沈信甫.
Product Manager @BitoGroup 幣託科技股份有限公司
2023 ~ Present
Product Manager
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規劃功能畫面包含 On Boarding flow、Dashboard 5. 研究 Google authenticator 二階段認證,保證產品安全 AI Project Manager 美商訊能集思科技 2019/2月/2月 Taipei, Taiwan JarviX 自然語言分析平台導入,並陪同業務進行產品功能的展示與簡報的介紹,並後續的 POC 驗證及相關 SPEC 撰寫,從資料的收集到
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Firebase Analytics
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4-6 years
國立臺北科技大學
互動設計所
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Data Engineer @美好金融
2022 ~ 2023
軟體工程師
Within two months
Java
Python
MongoDB
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6-10 years
國立中央大學
物理
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Software Developer @ZeroLogix
2022 ~ Present
前端工程師 Front-End Developer
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資訊管理學系,2018 年 8 月年 12 月 職位: 專任研究助理 畢業後繼續延伸論文的相關研究與協助碩班生論文的研究,開發結合自然語言與影像辦識問答系統。 使用技能: Python、Pytorch、OpenCV、NLP 學歷 國立中山大學資訊管理學系研究所,2017 年 6 月年 7 月 研究領域: 深
Python
React.js
Next.js
Employed
Open to opportunities
Full-time / Interested in working remotely
4-6 years
國立中山大學-資管系
資訊管理
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Avatar of Lewis Chang.
Senior Backend Engineer @Appier 沛星互動科技
2022 ~ Present
軟體工程師
Within one month
of 8 to deliver values to customers. - Coordinated communications among multiple stakeholders (PO, EM, QA, etc.) - Coached junior developers for both onboarding and enhancing code quality. - Introduced typing system by Typescript for better maintainability. - Migrated frontend framework from AngularJS to Angular. Software Engineer • AI4quant MaySepUsed NLP model and image processing help E-Commerce client to eliminate duplicate products. - Assessed NLP models for time series data. - Studied the state-of-the-art DL models like Efficient-Net, Transformer-XL. - Built a mobile app to receive data from various wearable devices via blue-tooth
Python
Backend Development
Frontend Development
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Not open to opportunities
Full-time
4-6 years
National Central University
Department of Optics and Photonics

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數據分析師 / Data Analyst
Logo of 同欣電子工業股份有限公司.
同欣電子工業股份有限公司
2023 ~ Present
台灣桃園
Professional Background
Current status
Employed
Job Search Progress
Professions
Data Analyst
Fields of Employment
Manufacturing
Work experience
4-6 years
Management
None
Skills
Python
JMP
SAS
Machine Learning
Deep Learning
Scikit-Learn
Tensorflow
Keras
MSSQL
MySQL
Oracle
MongoDB
Django
Flask
Plotly/Dash
Streamlit
Hadoop
Spark
Docker
Linux
PyTorch
XGBoost
Kafka
Git
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Database
Languages
English
Intermediate
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Data Analyst
Job types
Full-time
Locations
台灣桃園, 台灣新竹縣, 台灣新竹市
Remote
Interested in working remotely
Freelance
No
Educations
School
國立中山大學
Major
物理學系
Print

曹勝彥 Allen Tsao

嗨,我叫曹勝彥,來自台灣南投,大學就讀國立中山大學物理學系,畢業後因對數據科學/分析充滿熱情,參加了:「勞動部勞動力發展署-物聯網應用設計班」、和「財團法人資訊工業策進會-AI / Big Data 資料分析師養成班」,讓我有一定能力跨入數據科學/分析的領域。 

  1. 結訓後在「欣興電子」擔任智能大數據整合工程師,負責集團大數據技術路線規劃、推展、與建置,協助公司轉型邁入【工業4.0/智慧製造】; 
  2. 接著到「日月光半導體」擔任數據分析師,利用統計分析、機器學習等方法,協助製程單位分析數據、建立模型、數據化解讀製程參數分析結果,並協同轉化成可執行方案、追蹤方案成效;協助工廠掌握生產/設備狀況,以提高競爭力; 
  3. 目前在「同欣電子工業」擔任數據分析師,藉由工作深化技能與能力,並持續累積半導體封裝與測試產業(領域)知識。 
 工作的意義不在盡可能賺更多錢,而是在去做你喜歡的、能讓你每天早上開心起床的事,如有更好的工作/合作機會,歡迎通知我。
Hello, I'm Allen Tsao from Nantou, Taiwan. I'm currently a student majoring in Physics at National Sun Yat-sen University. After graduation, I developed a strong passion for data science and analysis. I pursued additional training to gain the skills needed to enter the field. I completed the "IoT Application Design Program" offered by the Ministry of Labor's Workforce Development Agency and the "AI/Big Data Data Analyst Training Program" by the Institute for Information Industry.  
  1. After completing my training, I worked as an Intelligent Big Data Integration Engineer at 「Unimicron」, where I was responsible for planning, promoting, and establishing the group's big data technical roadmap. I also assisted the company in transitioning into Industry 4.0 and smart manufacturing. 
  2. Subsequently, I joined 「ASE Group」 as a Data Analyst. In this role, I used statistical analysis and machine learning techniques to help process units analyze data, build models, and interpret process parameter analysis results. I collaborated on turning these results into executable plans and tracking their effectiveness. My work also involved helping the factory gain insights into production and equipment conditions to enhance competitiveness. 
  3. I am currently working as a Data Analyst at 「Tong Hsing Electronic」, where I continue to deepen my skills and knowledge in the semiconductor packaging and testing industry.
To me, the significance of work is not solely about earning more money but doing what you love and waking up happy every morning. If there are better job or collaboration opportunities, please feel free to reach out to me.

數據分析師 / Data Analyst 
新竹縣竹北市, 台灣 / Hsinchu County, Zhubei City, TW
  • Cell Phone: 0928-743748


工作經歷

 -「所有的經驗,都是人生的養分,會在意想不到之處,發揮作用。 」

同欣電子工業股份有限公司, 數據分析師(Data Analyst), 

Oct 2023 ~ Now

  1. 進行資料收集、標籤定義與數據清理
  2. 依據分析需求,進行資料數據分析與邏輯運算作業
  3. 數據視覺化報表產出,製作相關簡報
  4. 有效利用分析結果,提供單位擬定決策
  5. 跨部門溝通與需求訪談
  1. Collecting data, defining labels, and cleaning data.
  2. Performing data analysis and logical operations based on analytical needs.
  3. Generating data visualization reports and creating related presentations.
  4. Effectively utilizing the analysis results to assist the department in making decisions.
  5. Communicating across departments and conducting requirement interviews.

日月光半導體製造股份有限公司, 數據分析師(Data Analyst), 

May 2021 ~ Oct 2023

  1. 使用統計、機器學習等方法和分析工具協助工廠掌握生產/設備狀況,以提高競爭力
  2. 協助製程單位分析數據、建立模型、數據化解讀製程參數分析結果,並協同轉化成可執行方案,並追蹤方案成效
  3. 利用數據分析與儀表板設計軟體將分析的結果進行資料視覺化
  4. 專案執行與各單位溝通協調
  1. Assist the factory in understanding production/equipment conditions and enhancing competitiveness using statistical, machine learning, and other analytical tools.
  2. Aid process units in data analysis, model building, and data-driven interpretation of process parameter analysis results. Collaboratively transform these into executable plans and track their effectiveness.
  3. Utilize data analysis and dashboard design software for data visualization of analysis results.
  4. Execute projects and communicate and coordinate with various units.

欣興電子股份有限公司 , 【工業4.0/智慧製造】智能大數據整合工程師, 

Apr 2020 ~ May 2021

  1. 負責集團大數據技術路線規劃、推展、與建置
  2. 負責集團大數據資料探勘、挖掘、整併、預處理、運算、管理、與分析
  3. 各項製程良率報表開發,以及圖表繪製分析
  4. 分析集團機台生產數據,運用統計分析方法及機器學習提出適合演算模型,並建置分析模型,提供工廠營運改善建議
  1. Responsible for planning, promoting, and establishing the group's big data technical roadmap.
  2. Responsible for data exploration, mining, integration, preprocessing, computation, management, and analysis of the group's big data.
  3. Developing yield reports for various processes and creating charts for analysis.
  4. Analyzing production data from group machines, using statistical analysis methods and machine learning to propose suitable algorithm models, and establishing analytical models to provide operational improvement recommendations to the factory.

資策會_財團法人資訊工業策進會, AI / Big Data 資料分析師養成班 - 學員, 

Jun 2019 ~ Nov 2019

共計670小時:
  1. 關聯式資料庫,30小時
  2. 資料倉儲與商業智慧,24小時
  3. 巨量資料分析技術與工具應用,84小時
  4. 巨量資料儲存與處理,30小時
  5. 資料採礦分析,30小時
  6. NoSQL,24小時
  7. 物件導向系統分析與設計(UML),36小時
  8. 網路爬蟲,60小時
  9. Python程式設計與資料分析實作,66小時
  10. R軟體與資料探勘,24小時
  11. 專題實作,180小時
  12. Python程式設計及AI人工智慧導論,82小時
結訓專題:利用機器學習、深度學習在影像上的處理和辨識、配合消費者對商品的評分、點擊行為建立推薦系統,幫助使用者快速找到與自己喜好類似的鞋款外觀樣式。

In total, 670 hours of training were completed, including:
  1. Relational Databases: 30 hours
  2. Data Warehousing and Business Intelligence: 24 hours
  3. Big Data Analysis Techniques and Tools: 84 hours
  4. Big Data Storage and Processing: 30 hours
  5. Data Mining Analysis: 30 hours
  6. NoSQL: 24 hours
  7. Object-Oriented System Analysis and Design (UML): 36 hours
  8. Web Scraping: 60 hours
  9. Python Programming and Data Analysis Implementation: 66 hours
  10. R Software and Data Mining: 24 hours
  11. Project Implementation: 180 hours
  12. Python Programming and Introduction to AI (Artificial Intelligence): 82 hours
The training project involved the use of machine learning and deep learning for image processing and recognition. It incorporated consumer ratings and click behavior to create a recommendation system, helping users quickly find shoe styles that match their preferences.

私人工作室, 金融研究員, 

Apr 2018 ~ Jun 2019

  1. 經濟數據蒐集及資料庫建立,Python相關應用程式開發與維護
  2. 數量統計分析、策略研發
  3. 全球總體經濟、股市商品及產業研究,並撰寫分析專題報告
  4. 其他金融新創開發暨研究相關事務
  5. 主管交辧事項
利用網路爬蟲爬取網站股價資訊+作圖分析,找尋符合設想條件之挑資標的,架設網站並定期更新,從事資料蒐集、分析、撰寫研究報告之工作,同時須隨時注意大環境中可能影響獲利的各項經濟因素,以提供進行投資決策時的參考。
  1. Collecting economic data and establishing databases, developing and maintaining Python-related applications.
  2. Conducting quantitative statistical analysis and strategy development.
  3. Researching global macroeconomics, stock and commodity markets, and industries, and writing analytical research reports.
  4. Engaging in other financial innovation and research-related tasks.
  5. Supervising delegated tasks.
Using web scraping to gather stock price information from websites and conducting chart analysis to identify potential investment targets that meet specified criteria. Building and regularly updating a website for data collection, analysis, and research report writing. Concurrently, staying vigilant about various economic factors in the larger environment that could affect profitability, providing reference for investment decision-making.

勞動部勞動力發展署北基宜花金馬分署, 物聯網應用設計班 - 學員, 

Apr 2018 ~ Sep 2018

共計920小時:
  1. Linux作業系統,40小時
  2. 微控制器原理與應用,40小時
  3. 電子電路學,32小時
  4. C語言實習,61小時
  5. 網頁設計實習,40小時
  6. 感測器應用實習,60小時
  7. 專題實作,24小時
  8. 硬體操作實務與維護,69小時
  9. 電腦繪圖(電路圖),80小時
  10. 積體電路設計與應用,40小時
  11. 網頁圖文編輯設計實作,24小時
  12. APP程式設計與應用,40小時
  13. VHDL程式設計,32小時
  14. 數位乙級術科實作,56小時
  15. 網路與網站架設實習,44小時
  16. 電子工作法(儀表操作),20小時
  17. 數位邏輯電路實習,36小時
  18. 儀表操作,28小時
  19. 檢定實作練習,103小時
In total, 920 hours of training were completed, including:
  1. Linux Operating System: 40 hours
  2. Microcontroller Principles and Applications: 40 hours
  3. Electronics Circuitry: 32 hours
  4. C Language Practice: 61 hours
  5. Web Design Practice: 40 hours
  6. Sensor Applications Practice: 60 hours
  7. Project Implementation: 24 hours
  8. Hardware Operations and Maintenance: 69 hours
  9. Computer Graphics (Circuit Diagrams): 80 hours
  10. Integrated Circuit Design and Applications: 40 hours
  11. Web Graphics and Layout Design Practice: 24 hours
  12. App Programming and Applications: 40 hours
  13. VHDL Programming: 32 hours
  14. Digital Electronics Practical Skills: 56 hours
  15. Network and Website Construction Internship: 44 hours
  16. Electronic Work Practices (Instrument Operation): 20 hours
  17. Digital Logic Circuit Practical Skills: 36 hours
  18. Instrument Operation: 28 hours
  19. Certification Exam Practical Training: 103 hours


學歷

國立中山大學, 學士學位, 物理學系

2012.09 ~ 2016.06

【活動和社團】

  • 物理系桌-隊長
  • 桌球校隊-隊員

Pjnzjkm3ytqp9faqkjqh

專長


資料工程(Data Engineering) 

  • 資料預處理與分析(Data ETL/Analysis) 
    1. Python:Pandas、Dask、Numpy、Scipy、Pandas Profiling... 
    2. SAS:JMP 
  • 資料探勘(Data Mining) 
    1.  關聯/非關聯資料庫(SQL/NoSQL):Pyodbc、Cx_Oracle、Pymongo 
    2. 網頁自動化測試與爬蟲(Web Automation/Testing/Crawler):Selenium、Beautifulsoup4、Scrapy


資料視覺化(Data Visualization)

  • 圖表(Chart):Matplotlib、Seaborn、Bokeh、Plotly、Pydot 
  • 網頁應用框架(Web Application Framework):Django、Flask、Fastapi、Plotly Dash、Streamlit 
  • 網頁設計(Web Design):HTML、CSS、JavaScript、Bootstrap 
  • 投影片簡報(PowerPoint):Python-pptx 
  • 試算表(Excel):Xlsxwriter


人工智慧(Artificial Intelligence, AI)

  • 機器學習(Machine Learning, ML) / 深度學習(Deep Learning, DL):Scikit-Learn、TensorFlow、Keras、PyTorch、XGBoost 
  • AutoML:SAS Viya、AutoKeras、H2O


資料庫/大數據框架(Database/BigData Framework) 

  • 資料庫(Database) 
    1. 關聯式資料庫(SQL):MS SQL、Oracle 
    2. 非關聯式資料庫(NoSQL):MongoDB、Redis 
  •  大數據框架(BigData Framework) 
    1. Hadoop:建立多台電腦組成的叢集,以更快地平行分析大型資料集(Building a cluster of multiple computers to parallelly analyze large datasets for faster processing) 
    2. Spark:採用記憶體內快取並將查詢執行最佳化,以快速分析查詢任何規模的資料(Employing in-memory caching and query optimization for quick analysis of data of any scale) 
    3. Kafka:處理即時資料提供一個統一、高吞吐、低延遲的平台(Handling real-time data to provide a unified, high-throughput, low-latency platform)


系統開發建置(System Development)

  • 產品面向(Product Level) 
    1. 統計製程管理(Statistical Process Control, SPC) 
    2. 配方管理系統(Recipe Management System, RMS) 
    3. 良率管理系統(Yield Management System, YMS) 
  • 過程面向(Shop Floor Level) 
    1. 失效偵測與分類(Fault Defection and Classification, FDC) 
    2. 設備預防保養管理系統(Preventative Maintenance System, PMS) 
    3. 工程/探索式資料分析(Engineer/Exploratory Data Analysis, EDA) 
    4. 即時監控機制及設備健康預診斷與管理(Prognostic and Health Management, PHM) 
  • 未來持續發展方向(To Be Continued) 
    1. 全自動虛擬量測(Automatic Virtual Metrology, AVM) 
    2. 智慧型預測保養機制(Predictive Maintenance, PdM) 
    3. 先進製程控制(Advance Process Control, APC)


其他(Others)

  • 作業系統(OS):Linux 
  • 容器化(Container):Docker 
  • 版本控制(Version Control):Git、Github、GitLab

Resume
Profile

曹勝彥 Allen Tsao

嗨,我叫曹勝彥,來自台灣南投,大學就讀國立中山大學物理學系,畢業後因對數據科學/分析充滿熱情,參加了:「勞動部勞動力發展署-物聯網應用設計班」、和「財團法人資訊工業策進會-AI / Big Data 資料分析師養成班」,讓我有一定能力跨入數據科學/分析的領域。 

  1. 結訓後在「欣興電子」擔任智能大數據整合工程師,負責集團大數據技術路線規劃、推展、與建置,協助公司轉型邁入【工業4.0/智慧製造】; 
  2. 接著到「日月光半導體」擔任數據分析師,利用統計分析、機器學習等方法,協助製程單位分析數據、建立模型、數據化解讀製程參數分析結果,並協同轉化成可執行方案、追蹤方案成效;協助工廠掌握生產/設備狀況,以提高競爭力; 
  3. 目前在「同欣電子工業」擔任數據分析師,藉由工作深化技能與能力,並持續累積半導體封裝與測試產業(領域)知識。 
 工作的意義不在盡可能賺更多錢,而是在去做你喜歡的、能讓你每天早上開心起床的事,如有更好的工作/合作機會,歡迎通知我。
Hello, I'm Allen Tsao from Nantou, Taiwan. I'm currently a student majoring in Physics at National Sun Yat-sen University. After graduation, I developed a strong passion for data science and analysis. I pursued additional training to gain the skills needed to enter the field. I completed the "IoT Application Design Program" offered by the Ministry of Labor's Workforce Development Agency and the "AI/Big Data Data Analyst Training Program" by the Institute for Information Industry.  
  1. After completing my training, I worked as an Intelligent Big Data Integration Engineer at 「Unimicron」, where I was responsible for planning, promoting, and establishing the group's big data technical roadmap. I also assisted the company in transitioning into Industry 4.0 and smart manufacturing. 
  2. Subsequently, I joined 「ASE Group」 as a Data Analyst. In this role, I used statistical analysis and machine learning techniques to help process units analyze data, build models, and interpret process parameter analysis results. I collaborated on turning these results into executable plans and tracking their effectiveness. My work also involved helping the factory gain insights into production and equipment conditions to enhance competitiveness. 
  3. I am currently working as a Data Analyst at 「Tong Hsing Electronic」, where I continue to deepen my skills and knowledge in the semiconductor packaging and testing industry.
To me, the significance of work is not solely about earning more money but doing what you love and waking up happy every morning. If there are better job or collaboration opportunities, please feel free to reach out to me.

數據分析師 / Data Analyst 
新竹縣竹北市, 台灣 / Hsinchu County, Zhubei City, TW
  • Cell Phone: 0928-743748


工作經歷

 -「所有的經驗,都是人生的養分,會在意想不到之處,發揮作用。 」

同欣電子工業股份有限公司, 數據分析師(Data Analyst), 

Oct 2023 ~ Now

  1. 進行資料收集、標籤定義與數據清理
  2. 依據分析需求,進行資料數據分析與邏輯運算作業
  3. 數據視覺化報表產出,製作相關簡報
  4. 有效利用分析結果,提供單位擬定決策
  5. 跨部門溝通與需求訪談
  1. Collecting data, defining labels, and cleaning data.
  2. Performing data analysis and logical operations based on analytical needs.
  3. Generating data visualization reports and creating related presentations.
  4. Effectively utilizing the analysis results to assist the department in making decisions.
  5. Communicating across departments and conducting requirement interviews.

日月光半導體製造股份有限公司, 數據分析師(Data Analyst), 

May 2021 ~ Oct 2023

  1. 使用統計、機器學習等方法和分析工具協助工廠掌握生產/設備狀況,以提高競爭力
  2. 協助製程單位分析數據、建立模型、數據化解讀製程參數分析結果,並協同轉化成可執行方案,並追蹤方案成效
  3. 利用數據分析與儀表板設計軟體將分析的結果進行資料視覺化
  4. 專案執行與各單位溝通協調
  1. Assist the factory in understanding production/equipment conditions and enhancing competitiveness using statistical, machine learning, and other analytical tools.
  2. Aid process units in data analysis, model building, and data-driven interpretation of process parameter analysis results. Collaboratively transform these into executable plans and track their effectiveness.
  3. Utilize data analysis and dashboard design software for data visualization of analysis results.
  4. Execute projects and communicate and coordinate with various units.

欣興電子股份有限公司 , 【工業4.0/智慧製造】智能大數據整合工程師, 

Apr 2020 ~ May 2021

  1. 負責集團大數據技術路線規劃、推展、與建置
  2. 負責集團大數據資料探勘、挖掘、整併、預處理、運算、管理、與分析
  3. 各項製程良率報表開發,以及圖表繪製分析
  4. 分析集團機台生產數據,運用統計分析方法及機器學習提出適合演算模型,並建置分析模型,提供工廠營運改善建議
  1. Responsible for planning, promoting, and establishing the group's big data technical roadmap.
  2. Responsible for data exploration, mining, integration, preprocessing, computation, management, and analysis of the group's big data.
  3. Developing yield reports for various processes and creating charts for analysis.
  4. Analyzing production data from group machines, using statistical analysis methods and machine learning to propose suitable algorithm models, and establishing analytical models to provide operational improvement recommendations to the factory.

資策會_財團法人資訊工業策進會, AI / Big Data 資料分析師養成班 - 學員, 

Jun 2019 ~ Nov 2019

共計670小時:
  1. 關聯式資料庫,30小時
  2. 資料倉儲與商業智慧,24小時
  3. 巨量資料分析技術與工具應用,84小時
  4. 巨量資料儲存與處理,30小時
  5. 資料採礦分析,30小時
  6. NoSQL,24小時
  7. 物件導向系統分析與設計(UML),36小時
  8. 網路爬蟲,60小時
  9. Python程式設計與資料分析實作,66小時
  10. R軟體與資料探勘,24小時
  11. 專題實作,180小時
  12. Python程式設計及AI人工智慧導論,82小時
結訓專題:利用機器學習、深度學習在影像上的處理和辨識、配合消費者對商品的評分、點擊行為建立推薦系統,幫助使用者快速找到與自己喜好類似的鞋款外觀樣式。

In total, 670 hours of training were completed, including:
  1. Relational Databases: 30 hours
  2. Data Warehousing and Business Intelligence: 24 hours
  3. Big Data Analysis Techniques and Tools: 84 hours
  4. Big Data Storage and Processing: 30 hours
  5. Data Mining Analysis: 30 hours
  6. NoSQL: 24 hours
  7. Object-Oriented System Analysis and Design (UML): 36 hours
  8. Web Scraping: 60 hours
  9. Python Programming and Data Analysis Implementation: 66 hours
  10. R Software and Data Mining: 24 hours
  11. Project Implementation: 180 hours
  12. Python Programming and Introduction to AI (Artificial Intelligence): 82 hours
The training project involved the use of machine learning and deep learning for image processing and recognition. It incorporated consumer ratings and click behavior to create a recommendation system, helping users quickly find shoe styles that match their preferences.

私人工作室, 金融研究員, 

Apr 2018 ~ Jun 2019

  1. 經濟數據蒐集及資料庫建立,Python相關應用程式開發與維護
  2. 數量統計分析、策略研發
  3. 全球總體經濟、股市商品及產業研究,並撰寫分析專題報告
  4. 其他金融新創開發暨研究相關事務
  5. 主管交辧事項
利用網路爬蟲爬取網站股價資訊+作圖分析,找尋符合設想條件之挑資標的,架設網站並定期更新,從事資料蒐集、分析、撰寫研究報告之工作,同時須隨時注意大環境中可能影響獲利的各項經濟因素,以提供進行投資決策時的參考。
  1. Collecting economic data and establishing databases, developing and maintaining Python-related applications.
  2. Conducting quantitative statistical analysis and strategy development.
  3. Researching global macroeconomics, stock and commodity markets, and industries, and writing analytical research reports.
  4. Engaging in other financial innovation and research-related tasks.
  5. Supervising delegated tasks.
Using web scraping to gather stock price information from websites and conducting chart analysis to identify potential investment targets that meet specified criteria. Building and regularly updating a website for data collection, analysis, and research report writing. Concurrently, staying vigilant about various economic factors in the larger environment that could affect profitability, providing reference for investment decision-making.

勞動部勞動力發展署北基宜花金馬分署, 物聯網應用設計班 - 學員, 

Apr 2018 ~ Sep 2018

共計920小時:
  1. Linux作業系統,40小時
  2. 微控制器原理與應用,40小時
  3. 電子電路學,32小時
  4. C語言實習,61小時
  5. 網頁設計實習,40小時
  6. 感測器應用實習,60小時
  7. 專題實作,24小時
  8. 硬體操作實務與維護,69小時
  9. 電腦繪圖(電路圖),80小時
  10. 積體電路設計與應用,40小時
  11. 網頁圖文編輯設計實作,24小時
  12. APP程式設計與應用,40小時
  13. VHDL程式設計,32小時
  14. 數位乙級術科實作,56小時
  15. 網路與網站架設實習,44小時
  16. 電子工作法(儀表操作),20小時
  17. 數位邏輯電路實習,36小時
  18. 儀表操作,28小時
  19. 檢定實作練習,103小時
In total, 920 hours of training were completed, including:
  1. Linux Operating System: 40 hours
  2. Microcontroller Principles and Applications: 40 hours
  3. Electronics Circuitry: 32 hours
  4. C Language Practice: 61 hours
  5. Web Design Practice: 40 hours
  6. Sensor Applications Practice: 60 hours
  7. Project Implementation: 24 hours
  8. Hardware Operations and Maintenance: 69 hours
  9. Computer Graphics (Circuit Diagrams): 80 hours
  10. Integrated Circuit Design and Applications: 40 hours
  11. Web Graphics and Layout Design Practice: 24 hours
  12. App Programming and Applications: 40 hours
  13. VHDL Programming: 32 hours
  14. Digital Electronics Practical Skills: 56 hours
  15. Network and Website Construction Internship: 44 hours
  16. Electronic Work Practices (Instrument Operation): 20 hours
  17. Digital Logic Circuit Practical Skills: 36 hours
  18. Instrument Operation: 28 hours
  19. Certification Exam Practical Training: 103 hours


學歷

國立中山大學, 學士學位, 物理學系

2012.09 ~ 2016.06

【活動和社團】

  • 物理系桌-隊長
  • 桌球校隊-隊員

Pjnzjkm3ytqp9faqkjqh

專長


資料工程(Data Engineering) 

  • 資料預處理與分析(Data ETL/Analysis) 
    1. Python:Pandas、Dask、Numpy、Scipy、Pandas Profiling... 
    2. SAS:JMP 
  • 資料探勘(Data Mining) 
    1.  關聯/非關聯資料庫(SQL/NoSQL):Pyodbc、Cx_Oracle、Pymongo 
    2. 網頁自動化測試與爬蟲(Web Automation/Testing/Crawler):Selenium、Beautifulsoup4、Scrapy


資料視覺化(Data Visualization)

  • 圖表(Chart):Matplotlib、Seaborn、Bokeh、Plotly、Pydot 
  • 網頁應用框架(Web Application Framework):Django、Flask、Fastapi、Plotly Dash、Streamlit 
  • 網頁設計(Web Design):HTML、CSS、JavaScript、Bootstrap 
  • 投影片簡報(PowerPoint):Python-pptx 
  • 試算表(Excel):Xlsxwriter


人工智慧(Artificial Intelligence, AI)

  • 機器學習(Machine Learning, ML) / 深度學習(Deep Learning, DL):Scikit-Learn、TensorFlow、Keras、PyTorch、XGBoost 
  • AutoML:SAS Viya、AutoKeras、H2O


資料庫/大數據框架(Database/BigData Framework) 

  • 資料庫(Database) 
    1. 關聯式資料庫(SQL):MS SQL、Oracle 
    2. 非關聯式資料庫(NoSQL):MongoDB、Redis 
  •  大數據框架(BigData Framework) 
    1. Hadoop:建立多台電腦組成的叢集,以更快地平行分析大型資料集(Building a cluster of multiple computers to parallelly analyze large datasets for faster processing) 
    2. Spark:採用記憶體內快取並將查詢執行最佳化,以快速分析查詢任何規模的資料(Employing in-memory caching and query optimization for quick analysis of data of any scale) 
    3. Kafka:處理即時資料提供一個統一、高吞吐、低延遲的平台(Handling real-time data to provide a unified, high-throughput, low-latency platform)


系統開發建置(System Development)

  • 產品面向(Product Level) 
    1. 統計製程管理(Statistical Process Control, SPC) 
    2. 配方管理系統(Recipe Management System, RMS) 
    3. 良率管理系統(Yield Management System, YMS) 
  • 過程面向(Shop Floor Level) 
    1. 失效偵測與分類(Fault Defection and Classification, FDC) 
    2. 設備預防保養管理系統(Preventative Maintenance System, PMS) 
    3. 工程/探索式資料分析(Engineer/Exploratory Data Analysis, EDA) 
    4. 即時監控機制及設備健康預診斷與管理(Prognostic and Health Management, PHM) 
  • 未來持續發展方向(To Be Continued) 
    1. 全自動虛擬量測(Automatic Virtual Metrology, AVM) 
    2. 智慧型預測保養機制(Predictive Maintenance, PdM) 
    3. 先進製程控制(Advance Process Control, APC)


其他(Others)

  • 作業系統(OS):Linux 
  • 容器化(Container):Docker 
  • 版本控制(Version Control):Git、Github、GitLab