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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。

❝ 跨領域/非相關科系(具相關經驗)➤ 等你來挑戰 ❞ ｜台灣半導體封測 前 ①⓪ 大廠｜ ⑴ 華泰 好 薪情 ☞ 年薪上看 16 個月 ⑵ 華泰 友 職涯 ☞ 專屬輔導員/HR服務窗口 ⑶ 華泰 善 生活 ☞ 福利平台10,000+ 家廠商任你逛 (視營運狀況調整，固定或變動薪資因個人資歷或績效而異) 1.負責業務相關數據之收集、清理與統計分析，透過資料探勘找出潛在問題，並進行數據分析與視覺化、產出關鍵績效指標 (KPI)報表。 2.主導或協助推動組織內部碳盤查作業，規劃減碳路徑和能源管理策略，確保符合國際標準與法令規範。 3.評估並導入數位工具，推動流程自動化。 4.協助各單位推動數位化轉型與綠色環保專案，並提供相關技術諮詢。 5.根據數據分析結果，向管理層提供具備事實根據的業務改善方案。 6.協助與第三方驗證機構溝通，處理碳管理相關證照與標準之年度稽核。 ※【核定薪資範圍】不含加班及各項津貼※ 【具備以下證照尤佳】 淨零碳規劃管理師-初級能力鑑定免費模擬試題檢測

❝ 跨領域/非相關科系(具相關經驗)➤ 等你來挑戰 ❞ ｜台灣半導體封測 前 ①⓪ 大廠｜ ⑴ 華泰 好 薪情 ☞ 年薪上看 16 個月 ⑵ 華泰 友 職涯 ☞ 專屬輔導員/HR服務窗口 ⑶ 華泰 善 生活 ☞ 福利平台10,000+ 家廠商任你逛 (視營運狀況調整，固定或變動薪資因個人資歷或績效而異) 【工作內容】 1.大數據分析(資料清洗、分析、AI相關演算法建立) 2.資料收集與整理(熟悉ETL、Python、C#開發) 3.SQL資料庫管理 4.SPC系統開發維運及修改

Job Summary:The Statistician/Data Scientist will be responsible for all advanced statistical methods utilized for improving product quality, production yield, and factory effectiveness as well as finding the root-causes, along with other consulting services such as customer targeting and lead scoring in support of sales and marketing activities worldwide.Key Responsibilities:‧ Design, implement, and refine advanced statistical/Machine Learning models to support product quality improvement, increasing yield and factory effectiveness.‧ Cultivate strong relationships with production line engineers, IT, and other key stakeholders to ensure alignment of modeling initiatives with company objectives and to identify new hypotheses for model improvements.‧ Scale out modeling capacity by driving infrastructure improvements such as automation of data preparations, model training, implementation, and optimization.‧ Support integration of models into tools for use by product engineers and business analysts.‧ Engage with customers to develop and customized data analytics solutions to address special needs.‧ Address ad hoc queries from management and present actionable recommendations in a clear, concise, and convincing manner.‧ Communicate the application and benefits of using various predictive modeling techniques to improve decision-making to customers and stakeholders.‧ Collaborate effectively with team members, whether leading projects or supporting initiatives led by others. ‧ Provide direction, training, and guidance to less experienced team members.

【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！ Job Description 1. Analyze market sales data and seasonality to discover potential products. 2. Assist senior business managers in developing purchasing strategies to maintain inventory levels. 3. Track the sales performance of products. 4. Calculate the potential profits of products to provide the best purchase advice. 5. Maintain product profit margins through pricing strategies. 6. Improve workflows by collaborating with teams to design scalable, efficient solutions through data analysis and automation 7. Use data-analysis tools (e.g., SQL, Python, R Language) to identify root causes and validate ideas Requirements Improve workflows by collaborating with teams to design scalable, efficient solutions through data analysis and automation Use data-analysis tools (e.g., SQL, Python, R Language) to identify root causes and validate ideas Strong problem-solving skills

Job Summary/Role:The Big data developer team works closely with the manufacturing functions in all relative data fields, such as, 1) connecting and automating the data pipeline from MFG file servers, API, RDB, etc., 2) building structurally data warehouse and data market for flexible application or dashboard, and 3) also handling data cleansing and data governance. In order to accelerate the development of application/analysis, Big data developer will be the individual contributor with strong experience in the technologies of Big Data, Data warehouse, SQL and NoSQL etc. Also Big data developer will also work closely with data analysts/data scientists to solve the real MFG cases.Responsibility:‧ Collaborate with users, data analysts, data scientists to develop flowcharts, layouts and documents to identify solutions.‧ Architect on real MFG needs and translate requirements into technical needs.‧ Identify and understand the data sources that are relevant for analysis, and implement efficient data engineering functions (including data ingestion, cleaning, ETL, integration, etc.)‧ Consolidate the requirements and using data engineering skills to design a robust Data Mart.‧ Participate in design, architecture review and deployment of Big data and data warehouse solutions.‧ Design for automation and monitoring mechanism in a continuous integration environment.‧ Bring new data technology with POC to solve existing data challenges.‧ With high performance and comprehensive SQL to process data in relational databases (or Map/Reduce style querying for NoSQL databases).‧ Work closely with user/IT/data science team to design and develop scalable data pipeline or end-to-end analytical workflow.‧ Provide direction, training, and guidance to less experienced team members.

團隊組成 :前身是提供企業內部資料分析顧問服務以及打造客製化資料系統服務團隊之資料工程部門，擁有多年經驗。目前積極規畫與開發自有的資料處理平台，支撐高自由度、高效能、可靠並可擴展之資料處理/分析流程，解決實務上欲打造一套資料系統的難題。工作內容 (Responsibilities):1. Software Engineering:‧ Produce specifications and determine operational feasibility‧ Write well-designed and testable code for building an efficient and stable system‧ Troubleshoot, debug, maintain, and upgrade existing systems2. Data Platform Development Data Engineering:‧ Module development and integration for building a modern data platform‧ Efficient data flow/pipeline module design and Implementation‧ Work closely with data science team to integrate ML/statistical models and analytical workflow

1. Develop Cluster Deployment/Management/Monitor Modules2. Big Data Platform Operation (Hadoop, Spark, HBase, ...)3. Support Customer to Maintain Big Data Platform

"Job Summary:The Machine Learning engineer will be responsible for computer vision related projects, particularly in advanced image/video processing analyses and utilized for improving product quality, production yield, and factory effectiveness, along with other RD activities such as algorithm designs, prototype developments and experimental designs. Key Responsibilities:• Design, implement, and refine advanced Machine Learning/Deep Learning models to support product quality improvement, increasing yield and factory effectiveness.• Cultivate strong relationships with production line engineers, IT, and other key stakeholders to ensure alignment of modeling initiatives with company objectives and to identify new hypotheses for model improvements.• Scale out modeling capacity by driving infrastructure improvements such as automation of data preparations, model training, implementation, and optimization.• Apply deep learning and computer vision techniques, such as image classification, object detection, and support integration of models into tools for use by product engineers and business analysts.• Engage with customers to develop and customized data analytics solutions to address special needs.• Address ad hoc queries from management and present actionable recommendations in a clear, concise, and convincing manner.• Communicate the application and benefits of using various modeling techniques to improve decision-making to customers and stakeholders.• Collaborate effectively with team members, whether leading projects or supporting initiatives led by others. • Research and evaluate new data technology and state-of-art algorithms, and keep up to date with market trends and competitive insights."

1. Integrate and develop machine learning/mining modules.2. Plan data analysis flow based on customer requirement.3. Familiar with SAS, R, Matlab, Python, H2O, SparkML, …1. 整合和開發機器學習相關模組。2. 根據客戶需求，規劃資料分析流程。3. 熟悉相關分析元件 (SAS, R, Matlab, Python, H2O, SparkML, …)。