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2 到 4 年
4 到 6 年
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15 年以上
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University of Taipei
台北市立大學
臺北市立大學
Taipei, Taiwan
Taiwan
台灣
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New Taipei City, Taiwan
United States
新北市, 台灣
India
Taichung City, Taiwan
台中市, 台灣
Japan
Singapore
भारत
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Kaohsiung City, Taiwan
Taoyuan City, Taiwan
桃園市, 台灣
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C
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HTML/CSS
Java
JavaScript
JavaScript / ES6 / jQuery
Node.js
PYTHON
React.js
有
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一個月內
程式設計師
Bachelor’s Degree
大学
2016
在职中
Off
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好市多股份有限公司
緯創軟體股份有限公司
雄獅資訊股份有限公司
对远端工作有兴趣
没有符合的项目。
没有符合的项目。
English
4 到 6 年
6 到 10 年
10 到 15 年
15 年以上
Taipei, Taiwan
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Avatar of 陳旻琳.
Avatar of 陳旻琳.
陳旻琳
資深程式設計師 @緯創軟體股份有限公司
・
2022 ~ 现在
程式設計師
一個月內
Developed tools for team to improve efficiency of development routine. Side Project Frontend Development • Ｍinistry of Health and Welfare Added charts in cell therapy website of MOHW using jQuery. JunAugFrontend Development • Cambrian Soft Ltd. Developed CMS system for Someday Group using Vue 3. JanFebEducationUniversity of Taipei Computer Science Social Network Application Competition with NCCU, 2015, First place Outeaters - share your favorite meal: Built the project with team using Django framework. Graduate Presentation, 2016, Fifth place uOrder - Campus restaurant ordering system: Developed website by using Django framework and mobile app using Ionic (hybrid app framework).
JavaScript
JavaScript / ES6 / jQuery
HTML/CSS
全职 / 对远端工作有兴趣
6 到 10 年
台北市立大學
・
資訊科學

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兩個月內
Avatar of linsam.
linsam
Sr. Data Engineer
17LIVE
・
2021 ~ 现在
Taipei, 台灣
专业背景
目前状态
就职中
求职阶段
目前会考虑了解新的机会
专业
数据工程师, Python 开发人员, 系统架构
产业
资讯服务
工作年资
4 到 6 年
管理经历
无
技能
Python
MySQL
Linode
API Development
Linux
RabbitMQ
Celery
Nginx
Flask(Python)
Django(Python)
Git
docker swarm
Docker
docker-compose
Data Mining
Machine Learning
Traefik
Redis
ELK(ElasticSearch)
ELK
Prometheus
Grafana
Airflow
dolphindb
SQL
FastAPI
GKE
K8S
Real-Time Systems
GCP
语言能力
English
・
中阶
求职偏好
希望获得的职位
Data Solution Architect, Sr. Data Engineer, Data Engineer Manager
预期工作模式
全职
期望的工作地点
Taipei, 台灣, Taiwan
远端工作意愿
对远端工作有兴趣
接案服务
是，我利用业余时间接案
学历
学校
NDHU
主修科系
統計
列印
Profile 02 00@2x 71843ef6a0df47d6255a9c0436c409dcd5cd81f6514c51a6b2a93339d82bbff6

linsam

data engineer、backend engineer

 • 0972724528 •  台灣  •  [email protected]

5~6 years experience with data engineer and soft engineer. (Distributed Queue System, Database, Web Crawling, RESTful API, ETL, Docker, CICD, GCP, K8S, Airflow ...etc.)

1~2 years experience with data science. (data analysis, machine learning and deep learning)

Work Experience


17 Live -  Senior Data Engineer (IC5), May. 2021 - now

• Refactor ETL, create a airflow project by Cloud Composer to transfer ETL tools from digdag to airflow and transfer ETL develop method from shell script to python. 
• Maintenance BigQuery more than 100 tables. 
• Create pipelines from mysql and mongo to bigquery. 
• Create a good development culture, including the introduction of CICD, dev-stage-uat-master, release news, unit tests and test coverage. 
• Using Airflow unified scheduler job, like cloud function scheduler, BQ scheduler, crontab, and ML model by R or Python ...etc.
• Reduce Data Team 25% cost.
• Create Data Team's first real-time ETL system via GKE, Pub/Sub and Memorystore for sending push notifications to users.
• Create Data Team's first API via GKE for ML model, include achieve graceful shutdown, and run stress test via ApacheBench, and setup auto-scaling by hpa. 95% latency is under 200ms and RPS is over 200.
• Create a Tagging System for tracking groups of users. 
• Create a BigQuery Resource Monitor to monitor users BQ slot and query count usage. 
• Create document culture by confluence.
• The finalists of Break the Norm awards on 2021-Q3 and 2021-Q4. 
• Assist in interview more than 10 new data engineer. 
• Mentor junior data engineers to be more effective individual contributors.
• Apply the data team's models to the company's APP. (automatically send push notifications and in-app messages) 
• Automatically update recommend streamer list via data team's models to the company's APP.

SinoPac Holdings -  Software Engineer(Python), Nov. 2019 - May. 2021

• Develop python Api (shioaji) for stock/option/future place orde and account. 

• Develop C# Api (shioaji) for stock/option/future place orde and account, and setup CI/CD with GitHub actions.

• Deploy test system for simulate trading by docker swarm.

• Collecting distributed system Log by elk, grafana and prometheus. 13GB log data/daily.

• Monitor distributed system and alert chatbot.

• Develop a transaction-by-trade and odd lot trading API.

Open Up Summit Speaker ( FinMind ) - 2019-12-01

Tripresso - Data Engineer, Oct. 2018 - Nov. 2019 

• Analysis travel data and build a machine learning model. Estimating increase 3% orders (revenue). 

• Maintain and develop an ETL distributed queuing system with 20 machines. 

• Optimize the ETL system reduced more than 50% execution time. 

• Develop new product crawler let product volume increase 1.5%. 

• Making analysis BI charts provide for other departments.

Mandatory Military Service，Oct. 2017 - Oct. 2018

NDHU - RA, Mar. 2016 - Aug. 2017

Analysing G7 financial data. Model validation and parameter estimation by regression models ( SUR, MLE, Bootstrapping ). And comparing single equation estimators and confidence interval with system equation.

NDHU - TA, Sep. 2015 - Jul. 2017

Calculus, Linear Algebra, Statistics.

Projects

FinMind Open data Api


Open source financial data, more than 50 dataset, provide Api. 

More than 2,000 people registered.

2,000 stars on github.

Automatic update daily by docker swarm, distributed queue system rabbitmq and celery ( 10 cloud machines ). 

Total more than 1 billion data, 10 million streaming data per day.

Architecture diagram.


Bosch Production Line Performance - Kaggle Post-competition analysis, top 6% rank.

Highly imbalance data, ratio is 1000 : 1, 10 GB dataset size. And the data is 50% missing value. More than 4000 variables, but I build models by only 50 features.

Rossmann Store Sales - Kaggle 

Post-competition analysis, top 10% rank.

Time series problem. Building models predict sales after 48 days.

Grupo Bimbo Inventory Demand - Kaggle

Post-competition analysis, top 8% rank. 

Time series problem, eighty millions data size. Building models predict inventory demand after 2 weeks.

Instacart Market Basket Analysis - Kaggle

Real competition, top 25% rank. 

Predicting which products will an consumer purchase again.


 Verification code to text

Create python package of Taiwan Train Verification Code to text.

The model is made by keras-CNN.

Skills

Distributed Queue System

1. Rabbitmq & Celery & Flower. 

2. 8 nodes ( Cloud ) distributed queue system for web crawling. 

3. Deploy by Docker and GKE.

4. Graceful Shutdown.

Database

1. MySQL ( RDBMS ). 

2. Redis ( NoSQL ). 

3. Dolphindb ( TSDB ).

GCP

1. Pub/Sub.
2. GKE ( K8S ).
3. GCE.
4. BQ.
5. Composer.
6. MemoryStore.

CI/CD

1. Create automated tests and automated deploy for the FinMind team. 

2. Using gitlab runner. 

3. CD for auto publish python package. 

4. CD for auto update and deploy new version service.

Log Collect & Monitor

1. Distributed system log collect by elk.  

2. Prometheus and Grafana. Monitor user usage, request latency, request count 

3. Monitor by telegram bot and slackbot.

4. Monitor vm and container by Netdata and cadvisor.


data pipeline

1. Design data pipeline for crawler, backend and analysis by airflow.
2. Design more 200 ETL by airflow.
3. Build airflow by composer
4. Build a real-time pipeline for sending push notifications to users

Machine Learning

xgboost, random forest, svm. statistics - ols, lasso.

Web Crawling

1. Python - request, BeautifulSoup, lxml, selenium. 

2. Auto recognition captcha code by CNN model.

Data Mining

Python - numpy, pandas, sklearn. 

R - parallel, dplyr, data.table, mice.

WEB

1. https://finmindtrade.com/ 

2. nginx

3. frontend - vue 

4. backend - python 

5. traefik.

API

1. FastAPI.
2. Websocket.
3. Loading Balance.
4. Async.
5. Graceful Shutdown.

Stress Test 

1. ApacheBench.
2. Upper bound of FinMind api is 8000/minute request.


Education

National Dong Hwa University, Master of Science,  Sep. 2017.

Major : Mathematics and Statistics.

Tamkang University. Bachelor of Science, Sep. 2015.

Major : Mathematics

Languages

R, Python. Basic in English and proficient in Chinese.

简历
个人档案
列印
Profile 02 00@2x 71843ef6a0df47d6255a9c0436c409dcd5cd81f6514c51a6b2a93339d82bbff6

linsam

data engineer、backend engineer

 • 0972724528 •  台灣  •  [email protected]

5~6 years experience with data engineer and soft engineer. (Distributed Queue System, Database, Web Crawling, RESTful API, ETL, Docker, CICD, GCP, K8S, Airflow ...etc.)

1~2 years experience with data science. (data analysis, machine learning and deep learning)

Work Experience


17 Live -  Senior Data Engineer (IC5), May. 2021 - now

• Refactor ETL, create a airflow project by Cloud Composer to transfer ETL tools from digdag to airflow and transfer ETL develop method from shell script to python. 
• Maintenance BigQuery more than 100 tables. 
• Create pipelines from mysql and mongo to bigquery. 
• Create a good development culture, including the introduction of CICD, dev-stage-uat-master, release news, unit tests and test coverage. 
• Using Airflow unified scheduler job, like cloud function scheduler, BQ scheduler, crontab, and ML model by R or Python ...etc.
• Reduce Data Team 25% cost.
• Create Data Team's first real-time ETL system via GKE, Pub/Sub and Memorystore for sending push notifications to users.
• Create Data Team's first API via GKE for ML model, include achieve graceful shutdown, and run stress test via ApacheBench, and setup auto-scaling by hpa. 95% latency is under 200ms and RPS is over 200.
• Create a Tagging System for tracking groups of users. 
• Create a BigQuery Resource Monitor to monitor users BQ slot and query count usage. 
• Create document culture by confluence.
• The finalists of Break the Norm awards on 2021-Q3 and 2021-Q4. 
• Assist in interview more than 10 new data engineer. 
• Mentor junior data engineers to be more effective individual contributors.
• Apply the data team's models to the company's APP. (automatically send push notifications and in-app messages) 
• Automatically update recommend streamer list via data team's models to the company's APP.

SinoPac Holdings -  Software Engineer(Python), Nov. 2019 - May. 2021

• Develop python Api (shioaji) for stock/option/future place orde and account. 

• Develop C# Api (shioaji) for stock/option/future place orde and account, and setup CI/CD with GitHub actions.

• Deploy test system for simulate trading by docker swarm.

• Collecting distributed system Log by elk, grafana and prometheus. 13GB log data/daily.

• Monitor distributed system and alert chatbot.

• Develop a transaction-by-trade and odd lot trading API.

Open Up Summit Speaker ( FinMind ) - 2019-12-01

Tripresso - Data Engineer, Oct. 2018 - Nov. 2019 

• Analysis travel data and build a machine learning model. Estimating increase 3% orders (revenue). 

• Maintain and develop an ETL distributed queuing system with 20 machines. 

• Optimize the ETL system reduced more than 50% execution time. 

• Develop new product crawler let product volume increase 1.5%. 

• Making analysis BI charts provide for other departments.

Mandatory Military Service，Oct. 2017 - Oct. 2018

NDHU - RA, Mar. 2016 - Aug. 2017

Analysing G7 financial data. Model validation and parameter estimation by regression models ( SUR, MLE, Bootstrapping ). And comparing single equation estimators and confidence interval with system equation.

NDHU - TA, Sep. 2015 - Jul. 2017

Calculus, Linear Algebra, Statistics.

Projects

FinMind Open data Api


Open source financial data, more than 50 dataset, provide Api. 

More than 2,000 people registered.

2,000 stars on github.

Automatic update daily by docker swarm, distributed queue system rabbitmq and celery ( 10 cloud machines ). 

Total more than 1 billion data, 10 million streaming data per day.

Architecture diagram.


Bosch Production Line Performance - Kaggle Post-competition analysis, top 6% rank.

Highly imbalance data, ratio is 1000 : 1, 10 GB dataset size. And the data is 50% missing value. More than 4000 variables, but I build models by only 50 features.

Rossmann Store Sales - Kaggle 

Post-competition analysis, top 10% rank.

Time series problem. Building models predict sales after 48 days.

Grupo Bimbo Inventory Demand - Kaggle

Post-competition analysis, top 8% rank. 

Time series problem, eighty millions data size. Building models predict inventory demand after 2 weeks.

Instacart Market Basket Analysis - Kaggle

Real competition, top 25% rank. 

Predicting which products will an consumer purchase again.


 Verification code to text

Create python package of Taiwan Train Verification Code to text.

The model is made by keras-CNN.

Skills

Distributed Queue System

1. Rabbitmq & Celery & Flower. 

2. 8 nodes ( Cloud ) distributed queue system for web crawling. 

3. Deploy by Docker and GKE.

4. Graceful Shutdown.

Database

1. MySQL ( RDBMS ). 

2. Redis ( NoSQL ). 

3. Dolphindb ( TSDB ).

GCP

1. Pub/Sub.
2. GKE ( K8S ).
3. GCE.
4. BQ.
5. Composer.
6. MemoryStore.

CI/CD

1. Create automated tests and automated deploy for the FinMind team. 

2. Using gitlab runner. 

3. CD for auto publish python package. 

4. CD for auto update and deploy new version service.

Log Collect & Monitor

1. Distributed system log collect by elk.  

2. Prometheus and Grafana. Monitor user usage, request latency, request count 

3. Monitor by telegram bot and slackbot.

4. Monitor vm and container by Netdata and cadvisor.


data pipeline

1. Design data pipeline for crawler, backend and analysis by airflow.
2. Design more 200 ETL by airflow.
3. Build airflow by composer
4. Build a real-time pipeline for sending push notifications to users

Machine Learning

xgboost, random forest, svm. statistics - ols, lasso.

Web Crawling

1. Python - request, BeautifulSoup, lxml, selenium. 

2. Auto recognition captcha code by CNN model.

Data Mining

Python - numpy, pandas, sklearn. 

R - parallel, dplyr, data.table, mice.

WEB

1. https://finmindtrade.com/ 

2. nginx

3. frontend - vue 

4. backend - python 

5. traefik.

API

1. FastAPI.
2. Websocket.
3. Loading Balance.
4. Async.
5. Graceful Shutdown.

Stress Test 

1. ApacheBench.
2. Upper bound of FinMind api is 8000/minute request.


Education

National Dong Hwa University, Master of Science,  Sep. 2017.

Major : Mathematics and Statistics.

Tamkang University. Bachelor of Science, Sep. 2015.

Major : Mathematics

Languages

R, Python. Basic in English and proficient in Chinese.