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進階搜尋
On
4 到 6 年
6 到 10 年
10 到 15 年
15 年以上
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曾任
Career transition @Career Break
2024 ~ 2024
NLP Engineer / Data Scientist / Machine Learning Engineer
一個月內
Python
SQL
NLP
待業中
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
National Chengchi University
資訊科學系
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曾任
Data Engineer @Rooit Inc. (XO App)
2023 ~ 2023
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
一個月內
Python
Data Analysis
Data Science
待業中
正在積極求職中
全職 / 對遠端工作有興趣
6 到 10 年
中國醫藥大學(China Medical University)
臨床醫學研究所
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曾任
Senior Data Analyst @趨勢科技
2022 ~ 現在
Data Scientist, Data Analyst, Machine Learning Engineer
一個月內
Cathy Chen Sr. Data Analyst Senior data analyst with over 6 years experience in ETL, data visualization, exploratory data analysis, machine learning, deep learning, customized online dashboard using SQL , R , Python and data analytics tools. Data Scientist, Data Analyst Taipei, Taiwan [email protected] Experience Sr. Data Analyst • TrendMicro NovNow Work with cross-functional teams(UI/UX designer, Front-end, Back-end, Marketing, PM, Sales) to provide related data, design metrics, report and dashboard. Cross app data tracking and user journey analysis. VisionOne customers engagement score - the metrics can help fields to
python
R
SQL
待業中
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
輔仁大學 Fu Jen Catholic University
統計資訊學系
Avatar of 陳勤霖.
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曾任
博士後研究員 @洛桑大學神經發育疾病實驗室
2023 ~ 2023
Data Scientist, Data Analyst, Machine Learning Engineer
一個月內
學腦科學實驗室 1. 神經電生理訊號分析、神經細胞追蹤分析,與藥理試驗。 2. 研究論文撰寫與國際研討會的舉辦。 技能 Data Science Data Analysis, Image Analysis, Machine Learning, Deep Learning, Statistical Analysis, Data visualization Programming Python, PyTorch, NumPy, Pandas, Matplotlib, Scikit-Learn, Git, PostgreSQL, Docker Biotechnology Neuroscience, Genetics, Imaging, Scientific Writing Soft skill Project Management, Probelm Solving, Team Player, Proactive Communication 語言 English — 專業 Chinese — 母語或
Data Science
Data Analysis
Machine Learning
待業中
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
洛桑聯邦理工學院(EPFL)
神經科學
Avatar of 梁賦康 (Foo-Hong, Leong).
Avatar of 梁賦康 (Foo-Hong, Leong).
Product Manager @東元電機股份有限公司 (TECO Electric & Machinery Co. Ltd.)
2023 ~ 2023
Data Scientist, Data Analyst, Machine Learning Engineer
一個月內
started to learn Python in 2018 at TEDU and my first project was the Stock Trend Prediction by CNN. I kept using Python to implement web crawling, OOP, and Pandas in my job, intend to let my work become more automated. I used those techniques to automate the data-gathering problem, which shorten the existing progress duration. I'm very passionate about Data Scientist and Machine Learning. Work Experience Product Manager • 東元電機股份有限公司 (TECO Electric & Machinery Co. Ltd.) JanuaryOctoberProduct Analytics 2. Market Trend Analytics 3
Python
Power BI
Data Analytics
就職中
正在積極求職中
全職 / 對遠端工作有興趣
6 到 10 年
國立成功大學 National Cheng Kung University
Mechanical Engineering
Avatar of 李孟霖.
Avatar of 李孟霖.
資深資料工程師 @緯創資通股份有限公司
2020 ~ 現在
Data Analyst、Data Engineer、Data Scientist、Customer Experience Analyst、Solution Architect、Cloud Architect
一個月內
作經歷 緯創資通股份有限公司,2020 年 7 月年 3 月 「HR Digital Transformation Team Leader」 構想大型數位轉型專案,尋求資源並架構數位轉型藍圖 (構想Data Center、人才運營平台等數轉專案) Azure HR Domain 負責人;Power Platform HR Domain 負責人 ;one of Wistron Microsoft Copilot Top 300 users 具Power BI講師及實習生帶領經驗 「HR Data Center
python
PowerBI
Power Platform
就職中
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
元智大學 Yuan Ze University
工業工程與管理學所
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曾任
Data Analyst @趨勢科技 TrendMicro
2021 ~ 2024
Data Analyst、Data Engineer、Data Scientist、Customer Experience Analyst
一個月內
R
PL/SQL
Python
待業中
正在積極求職中
全職 / 對遠端工作有興趣
6 到 10 年
天主教輔仁大學 FU JEN CATHOLIC UNIVERSITY
金融所
Avatar of 陶俊良.
Avatar of 陶俊良.
資料分析師 Data Analyst @Portto 門戶科技| Blocto
2022 ~ 2024
Data Analyst、Data Engineer、Data Scientist、Customer Experience Analyst
一個月內
Portto 門戶科技| Blocto • 九月三 月 2024 Main Responsibilities: Establishing Data Pipeline Exploring new product features and competitor analysis on Dune Dashboard on the EVM User tagging for the Growth team (including Discord bot for monitoring Project details: Data Pipeline Regularly integrating client-side and BE data with external APIs and data collected by bots on Bigquery Establishing a systematic coding data table combined with Slack bot command manual and automatic data replenishment Daily data monitoring with Slack bot Planning client-side (app, sdk js) Amplitude event tracking to maximize data collection Using existing data to
python
R
MySQL
就職中
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
臺灣大學
流行病學與預防醫學所 生物統計組
Avatar of Vel Tien-Yun Wu.
Avatar of Vel Tien-Yun Wu.
Data Engineer @Groundhog Technologies Inc.
2021 ~ 2024
Data Analyst、Data Engineer、Data Scientist、Customer Experience Analyst
一個月內
Vel Tien-Yun Wu I bring 5 years of hands-on experience in data engineering and software development, with a focus on building scalable data processing systems utilizing Hadoop, Spark, Kafka and Docker. My expertise in developing efficient ETL pipelines has been fundamental in optimizing data workflows for various data warehouses, enhancing data integrity and availability. My track record includes managing high-volume data pipelines, automating scheduling processes to improve operational efficiency, and deploying monitoring solutions that have reduced Mean-Time-To-Repair (MTTR) by 40%. I have a strong foundation in SQL, especially PostgreSQL, which enables
Git
Python
Scala
就職中
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
University of Illinois at Urbana-Champaign, School of Information Sciences
Information Management
Avatar of Evan Wu.
Avatar of Evan Wu.
Back End Devel0per @英仕國際
2020 ~ 現在
Data Analyst 數據分析師 / Data Scientist 資料科學家
一個月內
Evan Wu Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet dolore magna aliquam erat volutpat. Ut wisi enim ad minim veniam, quis nostrud. Taiwan 工作經歷 Back End Devel0per • 英仕國際 三月Present Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet dolore magna aliquam erat volutpat. Java Software Developer • iiNumbers, Inc. / 木刻思股份有限公司 五月九月 2020 Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed
JAVA
Golang
SQL
就職中
正在積極求職中
全職 / 對遠端工作有興趣
10 到 15 年
National Chung Hsing University
Computer Science and Engineering

最輕量、快速的招募方案,數百家企業的選擇

搜尋履歷,主動聯繫求職者,提升招募效率。

  • 瀏覽所有搜尋結果
  • 每日可無限次數開啟陌生對話
  • 搜尋僅開放付費企業檢視的履歷
  • 檢視使用者信箱 & 電話
搜尋技巧
1
嘗試搜尋最精準的關鍵字組合
資深 後端 php laravel
如果結果不夠多,再逐一刪除較不重要的關鍵字
2
將須完全符合的字詞放在雙引號中
"社群行銷"
3
在不想搜尋到的字詞前面加上減號,如果想濾掉中文字,需搭配雙引號使用 (-"人資")
UI designer -UX
免費方案僅能搜尋公開履歷。
升級至進階方案,即可瀏覽所有搜尋結果(包含數萬筆覽僅在 CakeResume 平台上公開的履歷)。

職場能力評價定義

專業技能
該領域中具備哪些專業能力(例如熟悉 SEO 操作,且會使用相關工具)。
問題解決能力
能洞察、分析問題,並擬定方案有效解決問題。
變通能力
遇到突發事件能冷靜應對,並隨時調整專案、客戶、技術的相對優先序。
溝通能力
有效傳達個人想法,且願意傾聽他人意見並給予反饋。
時間管理能力
了解工作項目的優先順序,有效運用時間,準時完成工作內容。
團隊合作能力
具有向心力與團隊責任感,願意傾聽他人意見並主動溝通協調。
領導力
專注於團隊發展,有效引領團隊採取行動,達成共同目標。
超過一年
Data Scientist
KKday
2018 ~ 現在
Taiwan
專業背景
目前狀態
求職階段
專業
數據科學家
產業
工作年資
4 到 6 年工作經驗(1 到 2 年相關工作經驗)
管理經歷
技能
python programming
C++ Language
Machine Learning
Data Analysis
Matlab
TOEIC
Excel
語言能力
求職偏好
希望獲得的職位
機器學習工程師 / 資料分析工程師
預期工作模式
全職
期望的工作地點
Taipei City, 台灣, New Taipei City, 台灣
遠端工作意願
對遠端工作有興趣
接案服務
學歷
學校
主修科系
列印
Fn6ronatv0zic2wapqkh

江于萱

I majored in Probability theory, and focused on Markov Chain related problems. After graduation, I worked at ASUS on Zenfone camera algorithm development for 2 years. Then focus on self-learning platform "Coursera". I completed the series of class "Advanced Machine Learning". Now, I am a data scientist in KKday. The main projects are listed below :

  • Consultant for Marketing Department : already analysis over 20 topics for optimizing allocation of advertising expense.
  • Personalized city recommend on KKday homepage for increasing click rate over 1%.
  • Decreasing fraudulent for risk controlling department.

Machine Learning Engineer / Data Analysis Engineer / Data Scientist
Taipei,TW
[email protected]

Skills and Certifications


Language

  • Python 
  • C++


Mathematic

  • Probability 
  • Stochastic Process (Markov Chain) 
  •  Probability Model


Certifications

Coursera : Advanced Machine Learning

Work Experience

Data scientist at KKday : 1.5 years (2018/09~ ) 

Consultant for Marketing Department Objective: Optimize allocation of advertising expense (CID/EDM) 

  • Coupon 
  • Repurchase rate 
  • Customer behavior by locale 
  • Purchase platform (App/Mobile Web) 
Consultant for Risk Controlling Department 

  • Fraudulent (3D verification) 
  • Study the solution of other E-commerce 
Personal profile features on KKday.com 

  • Design city recommendation system (based on cookies) and launch this feature on KKday homepage since 2019/11. (Click rate increase over 1%) 
  • Design personal database for future project

Self study : 0.5 years (2018/03 ~ 2018/08) 

Study Advanced Machine Learning Specialization series classes ( 7 classes )

Software engineer at ASUS : 2.5 years (2015/10 ~ 2018/03)

Camera developer for Zenfone 

  • Design white balance algorithm (Based on RGB sensor) and launch this feature on Zenfone 3/4 series successfully. 
  •  Design camera automated manufacturing tool and has been deployed to factory (located at Suzhou, China) for producing Zenfone 3/4 and Zenbo successfully. 
  • Analysis the defeat of vendor (ex: Camera module, Samsung) and issues have been fixed successfully on Zenfone 4 Pro.

Student : ~ 2015/06

Master&Bachelor : National Chiao Tung University , Applied Mathematics 

Paragraph image 03 00@2x

KKday

Personalized city recommendation on KKday homepage. 

Based on language , customers purchase history and recently action, we generate cities interesting to customers. 

This model increased click rate over 1%.

Data Analytic - Purchase Platform

The target is comparing the value of customers who buy products on different platform. 

I analyze from three aspects : 

  • Average order price on different platform
  • Average value of customers with first order on different platform 
  • The preference of customers who have ordered on multiple platforms

Kaggle

This is a time model. For each time, it has only 5 features (shop_id/ item_id/ Category_name/ shop_name/ Category_id), So I need generate new features. I add  time delay data and embedding the shop name and item category as new features. I also train model to get new features. In the end, I use Linear model to reduce features and build 3 models to get the final answer.

Paragraph image 02 00@2x cb1a9cce8ec2420576e7f93d4a97d2663cb38d3060b7943702140d7f6da9f81e

Project 1 : Image Captioning

Given a picture, It will generate a short description for this picture.

This model use a pre-trained InceptionV3 model for CNN encoder and extract its last hidden layer as an embedding. 

Use about 82K training data and 40K validation date and each picture has 5 captions.

Paragraph image 00 00@2x ebb59a6d9adb03673d06762584bb6a0cc401a7cc4bd081bb82ce6f841d95aa2b
Paragraph image 01 00@2x 1a3881c875a7a1fb1e859435ef9363b5ddf36f4e73d1ad63a1a0af69f2a9f745

Project 2 : AI robot in Telegram

If you ask a programing problem, chat robot will return a closest StackOverflow link for you.

In this model, we will classify the training data to language type and use facebookresearch/StarSpace for embedding questions. For each input, we will classify it and embedding it to vector then found related link.

Project 3 : OpenAI CartPole-v0

Use Monte Coral tree search. That is, we choose road by root scores, if meet the tree leaf, do propagation (add score to root).

We can build a tree by playing games, then tree will tell us how to playing game. 

Paragraph image 00 00@2x ebb59a6d9adb03673d06762584bb6a0cc401a7cc4bd081bb82ce6f841d95aa2b
Paragraph image 01 00@2x 1a3881c875a7a1fb1e859435ef9363b5ddf36f4e73d1ad63a1a0af69f2a9f745

Project 4 : Playing Game

Use actor-critic training.

Input 4-frame image, train a DNN to catch the image information and predict the probability for 12 reactions. Then we according the DNN result to make a reaction for this game.

Master Thesis - A Random time for Simulating Markov Chains

In my master thesis, it provide a simulated method, which can avoid lots of computations, to make the Markov chain approximate its stationary distribution and also give a theorem to prove. At first part, we gave a theorem to prove the convergence of new random variable. For second part, we gave two special cases of simulation and found the random variable will not converge if the chain does not satisfy the condition of theorem. In the end, we provided a way to improve the chain.

履歷
個人檔案
Fn6ronatv0zic2wapqkh

江于萱

I majored in Probability theory, and focused on Markov Chain related problems. After graduation, I worked at ASUS on Zenfone camera algorithm development for 2 years. Then focus on self-learning platform "Coursera". I completed the series of class "Advanced Machine Learning". Now, I am a data scientist in KKday. The main projects are listed below :

  • Consultant for Marketing Department : already analysis over 20 topics for optimizing allocation of advertising expense.
  • Personalized city recommend on KKday homepage for increasing click rate over 1%.
  • Decreasing fraudulent for risk controlling department.

Machine Learning Engineer / Data Analysis Engineer / Data Scientist
Taipei,TW
[email protected]

Skills and Certifications


Language

  • Python 
  • C++


Mathematic

  • Probability 
  • Stochastic Process (Markov Chain) 
  •  Probability Model


Certifications

Coursera : Advanced Machine Learning

Work Experience

Data scientist at KKday : 1.5 years (2018/09~ ) 

Consultant for Marketing Department Objective: Optimize allocation of advertising expense (CID/EDM) 

  • Coupon 
  • Repurchase rate 
  • Customer behavior by locale 
  • Purchase platform (App/Mobile Web) 
Consultant for Risk Controlling Department 

  • Fraudulent (3D verification) 
  • Study the solution of other E-commerce 
Personal profile features on KKday.com 

  • Design city recommendation system (based on cookies) and launch this feature on KKday homepage since 2019/11. (Click rate increase over 1%) 
  • Design personal database for future project

Self study : 0.5 years (2018/03 ~ 2018/08) 

Study Advanced Machine Learning Specialization series classes ( 7 classes )

Software engineer at ASUS : 2.5 years (2015/10 ~ 2018/03)

Camera developer for Zenfone 

  • Design white balance algorithm (Based on RGB sensor) and launch this feature on Zenfone 3/4 series successfully. 
  •  Design camera automated manufacturing tool and has been deployed to factory (located at Suzhou, China) for producing Zenfone 3/4 and Zenbo successfully. 
  • Analysis the defeat of vendor (ex: Camera module, Samsung) and issues have been fixed successfully on Zenfone 4 Pro.

Student : ~ 2015/06

Master&Bachelor : National Chiao Tung University , Applied Mathematics 

Paragraph image 03 00@2x

KKday

Personalized city recommendation on KKday homepage. 

Based on language , customers purchase history and recently action, we generate cities interesting to customers. 

This model increased click rate over 1%.

Data Analytic - Purchase Platform

The target is comparing the value of customers who buy products on different platform. 

I analyze from three aspects : 

  • Average order price on different platform
  • Average value of customers with first order on different platform 
  • The preference of customers who have ordered on multiple platforms

Kaggle

This is a time model. For each time, it has only 5 features (shop_id/ item_id/ Category_name/ shop_name/ Category_id), So I need generate new features. I add  time delay data and embedding the shop name and item category as new features. I also train model to get new features. In the end, I use Linear model to reduce features and build 3 models to get the final answer.

Paragraph image 02 00@2x cb1a9cce8ec2420576e7f93d4a97d2663cb38d3060b7943702140d7f6da9f81e

Project 1 : Image Captioning

Given a picture, It will generate a short description for this picture.

This model use a pre-trained InceptionV3 model for CNN encoder and extract its last hidden layer as an embedding. 

Use about 82K training data and 40K validation date and each picture has 5 captions.

Paragraph image 00 00@2x ebb59a6d9adb03673d06762584bb6a0cc401a7cc4bd081bb82ce6f841d95aa2b
Paragraph image 01 00@2x 1a3881c875a7a1fb1e859435ef9363b5ddf36f4e73d1ad63a1a0af69f2a9f745

Project 2 : AI robot in Telegram

If you ask a programing problem, chat robot will return a closest StackOverflow link for you.

In this model, we will classify the training data to language type and use facebookresearch/StarSpace for embedding questions. For each input, we will classify it and embedding it to vector then found related link.

Project 3 : OpenAI CartPole-v0

Use Monte Coral tree search. That is, we choose road by root scores, if meet the tree leaf, do propagation (add score to root).

We can build a tree by playing games, then tree will tell us how to playing game. 

Paragraph image 00 00@2x ebb59a6d9adb03673d06762584bb6a0cc401a7cc4bd081bb82ce6f841d95aa2b
Paragraph image 01 00@2x 1a3881c875a7a1fb1e859435ef9363b5ddf36f4e73d1ad63a1a0af69f2a9f745

Project 4 : Playing Game

Use actor-critic training.

Input 4-frame image, train a DNN to catch the image information and predict the probability for 12 reactions. Then we according the DNN result to make a reaction for this game.

Master Thesis - A Random time for Simulating Markov Chains

In my master thesis, it provide a simulated method, which can avoid lots of computations, to make the Markov chain approximate its stationary distribution and also give a theorem to prove. At first part, we gave a theorem to prove the convergence of new random variable. For second part, we gave two special cases of simulation and found the random variable will not converge if the chain does not satisfy the condition of theorem. In the end, we provided a way to improve the chain.