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【Hour Loop 飛輪電商】在2013年成立，並於2022年初在美國那斯達克上市。作為亞馬遜 (Amazon) 第三方賣家，我們的工作不只廠商開發，還包括商品上架、價格制定，以及物流與庫存管理，通通一手包辦。 在百萬競爭對手中，我們透過獨特的營運模式，成功實現十年來的持續成長，並脫穎而出，在2022年底躍升為亞馬遜 (Amazon) 前十名的賣家！ 我們提供彈性且暢通的職涯管道，不綁年資，端看績效表現，從「獨立貢獻者」到「管理職」適性發展！如果你喜歡打磨自身專業能力，鑽研獨立的工作項目，便適合獨立貢獻者的角色；若你有準確遠見，善於溝通和帶領團隊，你可能就是未來的帶人主管！ 一、採購策略與商品管理 (約 70%)1. 分析市場銷售數據與季節性，發掘潛力商品並擬定相應的採購策略。2. 協助業務經理制定採購計畫，以維持合理的庫存水位。3. 持續追蹤商品銷售表現，計算潛在利潤並提供最佳採購建議。4. 透過價格策略維持並優化商品毛利率。5. 建立與分析銷售報表，辨識衰退品項並挖掘新的成長機會。二、流程優化與專案管理 (約 30%)1. 與跨部門合作，透過數據分析與自動化設計具擴展性與高效率的流程解決方案。2. 運用數據分析工具（Excel、SQL、Python、R 等）找出問題根因並驗證改善方案。3. 能獨立規劃並執行專案，於時程內交付具質量與影響力的成果。4. 善用內部系統工具，提出可行的流程優化建議並推動落地。任職條件1. 具 1–2 年以上相關工作經驗尤佳。2. 熟悉 Excel 基礎公式與功能（如：sum, count, xlookup, pivot, chart, VBA），具良好的數字敏感度；若具備 SQL 語法能力（如：JOIN, 欄位值轉換, 套件應用）及視覺呈現軟體（如：Looker, Tableau, PowerBI）則更佳。3. 具備獨立專案執行能力，能準時完成並交付成果。4. 擅長跨部門協調整合，並具備良好的數據分析與洞察能力。

Established in 1987 and headquartered in Taiwan, TSMC pioneered the pure-play foundry business model with an exclusive focus on manufacturing its customers’ products. As of 2024, TSMC serves more than 500 customers and manufactures over 11,000 products for high-performance computing, smartphones, the Internet of Things (IoT), automotive, and digital consumer electronics. It is the world’s largest provider of logic ICs, with an annual capacity of 16 million 12-inch equivalent wafers. TSMC operates fabs in Taiwan as well as manufacturing subsidiaries in Washington State, Japan and China, and the Company began construction on a specialty technology fab in Dresden, Germany, in 2024. In Arizona, TSMC is building three fabs, with the first starting 4nm production in 2025, the second by 2028, and the third by the end of the decade. Are you a creative IT professional with strong technical aptitude who embraces changes and is passionate about data and information? We invite you to join our highly innovative data engineering team which is constantly designing, developing, and delivering high quality solutions for our customers. As a data engineer, you will have opportunities to work in a dynamic and fast-paced environment to collaborate with business functions to design solutions. You will translate business requirements into technical needs, connect and automate data pipelines, and deliver data architecture and data governance solutions. Responsibility: Perform IT system architecture design, new technology research, and provide recommendation.Design and implement optimal data pipeline architecture (considered high data volume, data governance, etc.).Work with PRODUCT/BIZ teams to assist with new data platform re-engineering or data-related technical issues.DataOps high availability NoSQL DB (e.g.: Cassandra, S3/MinIO, MariaDB, etc.) on K8s environment.

Established in 1987 and headquartered in Taiwan, TSMC pioneered the pure-play foundry business model with an exclusive focus on manufacturing its customers’ products. As of 2024, TSMC serves more than 500 customers and manufactures over 11,000 products for high-performance computing, smartphones, the Internet of Things (IoT), automotive, and digital consumer electronics. It is the world’s largest provider of logic ICs, with an annual capacity of 16 million 12-inch equivalent wafers. TSMC operates fabs in Taiwan as well as manufacturing subsidiaries in Washington State, Japan and China, and the Company began construction on a specialty technology fab in Dresden, Germany, in 2024. In Arizona, TSMC is building three fabs, with the first starting 4nm production in 2025, the second by 2028, and the third by the end of the decade.Advanced Quality System Development (AQSD) is part of TSMC's Intelligent Manufacturing Center (IMC), responsible for three main directions: Use statistical methods and conditional monitoring to inspect fab control charts, providing early warning of abnormal product yields; offer a fab defense system settings comparison platform to check that machines meet the internal control anomaly conditions set by the engineering department.Develop online fab analysis platforms through Big Data, Machine Learning, and Deep Learning techniques for online yield/defect analysis to ensure the quality of wafers produced in the fab.Develop systems and provide logical operations to control and implement escape mechanisms for material batch changes, measurement stages, and inspection stages, ensuring quality and optimizing product sampling rules. Responsibilities: Apply machine learning/optimization algorithm to build up models for optimizing semiconductor production.Develop analysis and optimization methods to enhance product quality, increase tool productivity and improve people productivity.Design, develop and test prediction models with real applications in manufacturing.Build a flexible framework to speed up the development process of AI models, with a focus on Large Language Models (LLMs) serving.Turn exciting AI prototypes/ideas into products, leveraging LLMs and other advanced AI technologies.Develop next-generation AI backend systems related to large-scale real-time data access, collection, analytics and monitoring.Establish and maintain MLops processes and tools, including model deployment, monitoring, and automation.Continuously improve the quality of AI production systems, particularly those utilizing LLMs.

【職務說明】作為跨部門的數據夥伴，透過各項數據分析與洞察，協助進行產品與營運決策。需能將複雜且模糊的商業問題轉化為可量化的分析框架，並以資料視覺化、實驗設計與深度分析，提供具行動力與商業價值的建議，推動組織落實數據驅動的決策文化。【工作內容】1、跨部門商業夥伴合作 與產品、營運及行銷團隊密切協作，深入理解業務需求與關鍵痛點，將模糊的商業問題轉化為具體的分析框架，並追蹤核心指標達成狀況。2、資料視覺化與決策支援 規劃、設計並維護高互動性與高可用性的數據儀表板，將複雜數據轉化為直觀、可解讀的視覺化洞察，協助管理層即時掌握營運狀況與決策依據。3、實驗設計與成效評估 規劃與分析 A/B Testing，分析新功能、產品優化或營運活動之成效，透過統計方法與檢定結果，提出具體且可落地的優化建議。4、進階分析與洞察挖掘 進行探索式資料分析、歸因分析與關聯分析，找出影響關鍵指標的核心因素，為管理階層提供具統計顯著性與商業價值的量化洞察。5、數據洞察溝通與影響力輸出 定期產出分析報告與簡報，向跨部門與管理團隊傳達數據結論、商業影響與建議行動方案，促進跨部門共識，並推動組織內部的數據導向決策文化。必要條件:1、學歷背景：資訊、統計、數學、工業工程、經濟、商管或其他相關科系2、工作經驗：具備 1–2 年以上數據分析或相關領域經驗3、產業熱情與經驗： 熱愛影像處理、攝影或影片編輯領域，熟悉美圖系產品使用者行為者優先錄取。4、精通 SQL，能獨立撰寫複雜查詢處理海量數據。5、具備良好的商業敏感度（，能快速理解產品邏輯與營運情境，不僅僅是產出數字，更能提供策略建議。6、邏輯與溝通： 具備清晰的邏輯思考能力，能將複雜的數據分析結果轉化為非技術人員也能聽懂的語言。

客戶專案支援 Duties: This role will work closely with the team to handle inbound requests and expand our existing analytics system. A vast majority of the deliverables will be written in SQL. Responsibilities: •Handle triaged inbound requests; occasionally requires work directly with the stakeholders •Deliver one-off answers to critical analytics questions within the Hearables program, create ad-hoc scripts and gather the results for sharing •Maintain and develop our extensive analytics pipelines and dashboards

請至街口支付職缺網站進行投遞，我們會以此平台收到的履歷為主喔！【團隊與角色職責】 後端工程團隊隸屬於策略營運部門資料產品組的一部分，你將是推動資料產品與資料應用服務的重要工程夥伴，與資料分析師及產品技術相關部門密切協作。 參與資料產品規劃與開發，設計並建構滿足業務需求的資料產品與功能服務協助串接與整合跨部門資料需求，支援資料應用相關功能與應用場景參與資料平台基礎建設與資料流程維運，提升資料應用穩定性與效能透過技術思維優化資料存取方式，推動資料驅動產品與決策的實現與產品開發團隊共同設計可應用的資料功能 【為什麼要加入我們】 與資料分析、資料產品團隊緊密合作，打造具價值的資料服務與應用資料驅動決策的團隊文化，重視架構設計與資料治理品質有機會參與資料平台設計與技術選型，實踐工程解決資料問題的價值資料服務橫跨多部門，參與多樣化業務場景與資料產品發展

Kompas.com adalah salah satu pionir media online di Indonesia ketika pertama kali hadir di Internet pada 14 September 1995 dengan nama Kompas Online. Saat ini, kami mencari seorang Data Archivist yang akan bergabung dengan tim kami untuk mengkurasi dan mengarsipkan aset digitalmilik Kompascom antara lain: foto, video, dan footage.

Mengelola dan memastikan performa database tetap optimalMenjaga keamanan dan akses dataMelakukan monitoring, backup recovery dataMenangani kendala teknis terkait databaseMendukung kebutuhan data untuk operasional bisnis

🎯 Key Responsibilities (Jobdesk):- Data Pipeline Construction: Membangun, menguji, dan memelihara arsitektur pipeline data (ETL/ELT) yang skalabel.- Database Management: Mengoptimalkan struktur database dan query untuk memastikan performa sistem yang tinggi.- Data Integration: Mengintegrasikan berbagai sumber data (API, database internal, pihak ketiga) ke dalam Data Warehouse perusahaan.- System Monitoring: Memantau kesehatan infrastruktur data dan menangani kendala teknis (troubleshooting) yang muncul.- Collaboration: Bekerja sama dengan Data Scientist dan Data Analyst untuk menyediakan dataset yang siap digunakan untuk analisis.

1. Develop and implement databases, data collection systems, data analytics, and other strategies to optimize statistical efficiency and quality.2. Acquire data from primary or secondary sources and maintain databases/data systems.3. Interpret data, analyze results using statistical techniques, and provide ongoing reports as needed by stakeholders.4. Identify, analyze, and interpret trends or patterns in complex data sets.5. Filter and "clean" data by reviewing computer reports, printouts, and performance indicators to locate and correct system problems.6. Work with stakeholders to prioritize academic, financial, and human resource information needs.7. Locate and define new process improvement opportunities.8. Improve data quality across educational and business systems.9. Prepare reports, dashboards, and visualizations in consultation with stakeholders and advise and support as needed.10. Identify and recommend new ways to save time and money by streamlining business processes.