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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
United States
Data Engineer @Groundhog Technologies Inc.2021 ~ 2024
・
Data Analyst、Data Engineer、Data Scientist、Customer Experience Analyst
一個月內
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
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Information Management
Principal @Cascade Data Labs2016 ~ 2022
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Director Data
兩個月內
Emily Ledoux Delivery Principal Seasoned Delivery Principal in the Data Practice. Focused on designing robust, scalable data ecosystems in the cloud to feed insights and data visualizations. Well-rounded consultant with experience spanning sales, recruiting, and delivery. Proven Delivery & Client Lead. Portland, OR, USA https://www.linkedin.com/in/emily-ledoux/ Work Experience JanuaryPresent Principal Data Architect Kin + Carta Delivery or Client Lead for over 25 resources, including direct reports, delivery oversight, hours tracking, QBRs, onboarding management, budget ownership and related responsibilities. Cloud Architect, designing Azure and
就職中
・
目前會考慮了解新的機會
全職 / 對遠端工作有興趣
6 到 10 年
University of Pennsylvania
・
Economics就職中
全職 / 對遠端工作有興趣
4 到 6 年
國立政治大學
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Computer Science就職中
全職 / 對遠端工作有興趣
4 到 6 年
Government Engineering College
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Bachelor of Engineering
數據分析工程師 @ASE Group Global2022 ~ 現在
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PM/產品經理/專案管理
一個月內
蘇庭恩 Lyndon Su 數據分析/系統分析/專案管理 Mobile：Email： [email protected] 工作經歷 Data Analyst Engineer 日月光半導體製造股份有限公司 • 2022/09 - Present Responsibilities 1 數據倉儲PM｜ 部門數據倉儲規劃& Data Pipeline建立 管理部門內部報表人力支援分配與規劃 2 數據決策平台｜ 建立採購員議
就職中
・
目前會考慮了解新的機會
全職 / 對遠端工作有興趣
4 到 6 年
銘傳大學
・
應用統計資料科學學系
SQL Server Database Administrator & Linux Systems Administrator @OAG Analytics2019 ~ 現在
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SQL Server Database Administrator & Linux Systems Administrator
超過一年
Patrick Sandrin, Tchatchoua Mbada DevOps Engineer & Site reliability engineer & AWS Engineer & Linux Systems Administrator & SQL Database Administrator Houston, TX, [email protected] Experienced IT professional working for almost 10 years in the IT field. My knowledge and experience include: - SQL Database administrator (DBA) with about 10 years of production support experience in designing, testing and supporting next-generation database solutions in SQL Server environments (SQL server installation, implementation & migration - performance running & capacity monitoring - backup & recovery - failover cluster & always ON - Database maintenance - ETL - SSRS - SSAS - SSIS) - Linux Systems Administrator with about 6 years of experience in troubleshooting network
全職 / 對遠端工作有興趣
6 到 10 年
Ankara University
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Bachelor of Science, Computer Science
Technical Program Manager @Google2022 ~ 現在
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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
Kigo Chen Experienced Data Scientist with a demonstrated history of working in the semiconductors and E-commerce industry. As full-stack Data Scientist , specialized skills in systematic AI/ML solutions from data pipeline, modeling to serving with Scala/Python/Spark and also architecture design. Aim to turn data-driven evidence into bussiness-decision making with systematic AI/ML solutions for my clients. Micron Technology Sr. Data Science Engineer Taichung，TW Mail: [email protected] Working Experience Sr. Data Scientist Micron Technology, 2016/12 - Current As a technique lead
就職中
・
目前沒有興趣尋找新的機會
全職 / 對遠端工作有興趣
6 到 10 年
國立清華大學
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Statistics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
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
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。
專業背景
目前狀態
求職階段
專業
產業
工作年資
管理經歷
技能
語言能力
求職偏好
希望獲得的職位
預期工作模式
期望的工作地點
遠端工作意願
接案服務
學歷
學校
主修科系
Skills
Backend Data Systems
- API design: Developing RESTful APIs, lightweight query languages, real-time streaming over WebSockets
- ETL and archiving: Batch and streaming ingestion, selecting and optimizing databases for different access patterns, custom scripts to tame unruly datasets
- Tools: Python (Django, Flask, NumPy), Node.JS, Postgres + PostGIS, AWS Redshift
User Interface Engineering
- Single Page Applications: Creating browser applications with routing, text and map-based search, and OAuth login
- Data Visualization: Combining charts, maps, and text to provide interactive context about a dataset
- Tools: JavaScript (ES6), Ember, React, Sass, Leaflet, HighCharts
Cloud Infrastructure
- Continuous Delivery: Reliable feature delivery with build pipelines that run test suites and deploy updates across production servers
- Tools: AWS (EC2, Elastic Beanstalk, Lambda, Kinesis, and many more), Ansible, NGINX, Unix scripting
Experience & Education
Software Engineer | Sourceress | October 2017 - Present
Software Engineer | Argonne National Lab - Urban Center for Computation and Data | Sep 2015 - June 2017
Software Engineering Co-op | Rockwell Automation | Jan 2014 - Aug 2014
B.S. Computer Science | University of Pittsburgh | August 2011 - April 2015
Selected Projects
Sourceress
Artificial intelligence recruiter that uses tailor-made machine learning models to find great engineering candidates.
Engineer: October 2017 - Present
- Improved core infrastructure for combining human labels and machine learning-generated predictions to generate ratings on candidates.
- Co-wrote new search system that let contractors to perform complex searches over hundreds of thousands of candidate profiles in a few seconds (compared to old system which took minutes).
- Worked closely with business operations team to provide better metrics for contractor performance and develop features to improve contractor productivity.
Plenario (@Argonne National Lab)
Web application that enables space and time-based discovery of open data. Provides API for querying across datasets.
Lead Engineer: September 2015 - June 2017
- Took from prototype to production-ready application depended on by academic users and the City of Chicago's opengrid.io.
- Designed and implemented real-time data pipeline using AWS Kinesis, Lambda, and Redshift to ingest and stream data from the Array of Things sensor network.
- Built up engineering team by recruiting three new engineers and mentoring junior developers and interns.
- Improved response time of most important family of queries by a multiple of 10 by redesigning the database and optimizing client code.
- Rewrote ingestion process to improve reliability and scale with demand.
- Increased speed of feature delivery by migrating from hand-rolled EC2 instances with manual deployments to push-to-deploy with Elastic Beanstalk and Travis CI.
- Tools: Python (Flask), JavaScript (Ember for frontend, Node for streaming pipeline)
Community
Talks
- JavaScript for Data Analysts, March 2017
- Chapin Hall Center for Children
- Open Data, Open Government, Feb 2017
- PyData Chicago Meetup
- Databases for Smart Cities, Nov & Dec 2016
- Guest lecture at University of Chicago and DePaul University Masters database courses
- SQLAlchemy: Beyond ORM, Dec 2015
- Chicago Python Meetup
Volunteering
- PyData Chicago Meetup
- Build Night Host: Feb 2016 - Dec 2016
- Chicago Python Meetup
- Web Development Mentor: Spring 2016
Panels
- Open Data Roundtable on Public-Private Collaboration, June 2016
- White House Office of Science and Technology Policy
- International Symposium on Urban Living Labs, February 2016
- UK Collabatorium for Research on Infrastructure and Cities
Skills
Backend Data Systems
- API design: Developing RESTful APIs, lightweight query languages, real-time streaming over WebSockets
- ETL and archiving: Batch and streaming ingestion, selecting and optimizing databases for different access patterns, custom scripts to tame unruly datasets
- Tools: Python (Django, Flask, NumPy), Node.JS, Postgres + PostGIS, AWS Redshift
User Interface Engineering
- Single Page Applications: Creating browser applications with routing, text and map-based search, and OAuth login
- Data Visualization: Combining charts, maps, and text to provide interactive context about a dataset
- Tools: JavaScript (ES6), Ember, React, Sass, Leaflet, HighCharts
Cloud Infrastructure
- Continuous Delivery: Reliable feature delivery with build pipelines that run test suites and deploy updates across production servers
- Tools: AWS (EC2, Elastic Beanstalk, Lambda, Kinesis, and many more), Ansible, NGINX, Unix scripting
Experience & Education
Software Engineer | Sourceress | October 2017 - Present
Software Engineer | Argonne National Lab - Urban Center for Computation and Data | Sep 2015 - June 2017
Software Engineering Co-op | Rockwell Automation | Jan 2014 - Aug 2014
B.S. Computer Science | University of Pittsburgh | August 2011 - April 2015
Selected Projects
Sourceress
Artificial intelligence recruiter that uses tailor-made machine learning models to find great engineering candidates.
Engineer: October 2017 - Present
- Improved core infrastructure for combining human labels and machine learning-generated predictions to generate ratings on candidates.
- Co-wrote new search system that let contractors to perform complex searches over hundreds of thousands of candidate profiles in a few seconds (compared to old system which took minutes).
- Worked closely with business operations team to provide better metrics for contractor performance and develop features to improve contractor productivity.
Plenario (@Argonne National Lab)
Web application that enables space and time-based discovery of open data. Provides API for querying across datasets.
Lead Engineer: September 2015 - June 2017
- Took from prototype to production-ready application depended on by academic users and the City of Chicago's opengrid.io.
- Designed and implemented real-time data pipeline using AWS Kinesis, Lambda, and Redshift to ingest and stream data from the Array of Things sensor network.
- Built up engineering team by recruiting three new engineers and mentoring junior developers and interns.
- Improved response time of most important family of queries by a multiple of 10 by redesigning the database and optimizing client code.
- Rewrote ingestion process to improve reliability and scale with demand.
- Increased speed of feature delivery by migrating from hand-rolled EC2 instances with manual deployments to push-to-deploy with Elastic Beanstalk and Travis CI.
- Tools: Python (Flask), JavaScript (Ember for frontend, Node for streaming pipeline)
Community
Talks
- JavaScript for Data Analysts, March 2017
- Chapin Hall Center for Children
- Open Data, Open Government, Feb 2017
- PyData Chicago Meetup
- Databases for Smart Cities, Nov & Dec 2016
- Guest lecture at University of Chicago and DePaul University Masters database courses
- SQLAlchemy: Beyond ORM, Dec 2015
- Chicago Python Meetup
Volunteering
- PyData Chicago Meetup
- Build Night Host: Feb 2016 - Dec 2016
- Chicago Python Meetup
- Web Development Mentor: Spring 2016
Panels
- Open Data Roundtable on Public-Private Collaboration, June 2016
- White House Office of Science and Technology Policy
- International Symposium on Urban Living Labs, February 2016
- UK Collabatorium for Research on Infrastructure and Cities