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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。

▋▍About Us｜關於我們（醫療 X 科技） 用數據驅動決策，將生醫資訊轉化為生命的價值。 在慧康生技（Health2Sync），數據是我們最核心的資產。身為數據團隊的一員，你將有機會處理海量且多樣化的生醫數據（Biomedical Data），並透過機器學習與生成式 AI 技術，將其轉化為對用戶及醫療院所有實質幫助的數據產品。 我們不僅僅是技術的執行者，更是公司重大決策的參與者。在這裡，每一份分析報告都可能改變產品走向，每一條數據管線都在支撐全球百萬用戶的健康。期待對數據科學充滿熱忱的你加入，與我們一起用技術為病患與醫療人員創造更多可能性。 ▋▍Why Join Us｜為什麼加入我們 接觸稀缺的生醫大數據：處理真實世界（Real-World Data）的生理指標與健康數據，在技術深度之外，累積珍貴的醫療科技領域知識（Domain Know-how）。GenAI 與 LLM 實戰舞台：不只是開發傳統模型，你將主導基於大語言模型的應用開發，將最新的 AI 技術落地於數位健康場景。從基礎設施到產品落地：參與 Data Lakehouse 的架構設計與優化，親手建立支撐大規模運算與建模的高效率數據管線。高度影響力的決策參與：團隊推崇透明溝通與共創，你的分析結果與模型表現將直接影響產品的發展策略與商業方向。 ▋▍Role Highlights｜職缺亮點 數據科學的最前線：同時跨足數據工程與 AI 建模，讓你成為市面上最搶手的全方位數據專才。賦予數據生命感：看著你寫出的模型轉化為 App 上的健康建議，實質改善病患生活，這種成就感無可取代。純技術、零官僚：我們在乎的是數據的真實性與解決方案的有效性，提供最透明、最尊重專業的工程環境。接軌國際技術標準：與具備國際視野的團隊共事，使用最先進的數據架構處理跨國市場的挑戰。 ▋▍Responsibility｜主要職責 [ 數據基礎設施建構 ] 架構建立與維護：設計並持續優化數據基礎設施（Data Pipeline, Data Lakehouse），以支援高效的數據分析與機器學習建模。管線自動化：使用 Airflow/Dagster 構建穩定、可擴展的 Data Pipeline，並管理大數據儲存架構（如 Apache Iceberg）。 [ AI 與機器學習應用開發 ] 模型開發與部署：利用數位健康數據開發並部署機器學習、統計模型及生成式 AI (GenAI) 應用。LLM 應用實踐：針對產品需求，構建並維護基於大語言模型 (LLM) 的應用服務，提升產品智能化程度。系統性能優化：優化現有的 AI 系統與演算法，確保其在生產環境中的性能與可擴展性。 [ 數據決策支援 ] 跨團隊任務執行：運用分析工具與統計方法，支援產品與業務團隊的特定任務，將數據轉化為可執行的行動建議。數據專案推動：參與數據產品發想，持續探索能優化 H2 產品體驗的數據科學方案。 ▋▍Media Coverage｜媒體報導 《環球生技月刊》慧康生技明掛牌興櫃 《今周刊》打造智抗糖 App 攻入慢性病平台 《數位時代》台灣新創進軍韓國 《今周刊》慧康創業背景 《天下雜誌》台灣第一數位療法

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.

為什麼大家喜歡在 RichWell Co.Ltd. 上班？ 1.彈性上班-早上不趕打卡，想多睡一點、避開通勤人潮都OK。2.特休多多-不用等滿一年就能休假，我們比法規更大方，放假就是要爽爽的。3.獎金福利讚 年終、績效獎金該有的都有，努力絕對不白費。4.生日小驚喜，公司記得你的每個重要時刻。5.定期聚餐/Team Building 不只是工作夥伴，更是一起成長的戰友，吃吃喝喝感情更緊密。6.技術課、內部分享會，想學什麼我們都支持，讓你持續進化不退化！ Key Responsibilities for Data Analyst: Responsible for gathering data from various sources, including internal databases, user interactions third-party APIs, ensuring data accuracy and integrity.Perform exploratory and statistical analysis to identify trends, patterns, and correlations in large datasets.Create clear, compelling reports and dashboards to communicate insights of the product to stakeholders.Work closely with product and engineering teams to define key performance indicators (KPIs) and track product performance.Provide recommendations to improve software features, user engagement, and operational efficiency based on data findings.Implement processes to ensure data quality, consistency, and security, adhering to company policies and regulations.Conduct custom analyses to support strategic initiatives or respond to business questions.

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.

At SWAG Live's data team, our mission is to democratize data by building a self-service data platform. We aim to empower internal teams to access, interpret, and derive valuable insights from data effectively.As a Data Scientist in this role, you will collaborate with a multidisciplinary team of engineers and analysts to tackle diverse challenges using quantitative techniques such as statistical analysis and machine learning. You will work with large, complex event-based datasets, conduct exploratory data analysis (EDA), define requirements, and develop deploy models. We are particularly seeking a data scientist with experience in building customized recommendation models and a strong interest in product-focused machine learning development. Responsibilities Leverage state-of-the-art algorithms to build fully customized recommenders and other growth models.Design, deploy and maintain all components necessary for modeling, including feature engineering, automatic model training tuning and engineering toolchains.Create a comprehensive monitoring framework to evaluate model performance and provide actionable insights to drive business growth, focusing on awareness conversion and transactions.Understand stakeholder business requirements and design end-to-end machine learning/AI solutions that are effective, practical, and robust in addressing business challenges.Collaborate closely with data engineers and backend engineers to develop scalable systems.Communicate efficiently with cross-functional teams, promote the implementation of strategic applications, and drive continuous optimization.

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform. WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement. Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it. The Role: We are seeking an exceptionally talented data scientist with strong modeling and programming skills to join our team. In this role, you will work closely with data science team and technologists across the firm to develop appropriate features and metrics for data processing. Perform analysis and generate models of financial datasets using machine learning techniques Process, clean and verify the integrity of unstructured data and turn data into valuable insights Develop and create data that seek to predict the movement of financial market Transfer data into internal infrastructure applying variety of algorithmic techniques What You’ll Bring: Have a Master’s degree or higher from a leading university in Computer Science, Electrical Engineering or other related areas Good academic record Familiar with modeling, data structures, algorithms and optimizations Strong knowledge of machine/deep learning algorithms Proficient in programming languages of both C++ and Python Possess good communication and presentation skills in English Ability to work independently and as member of a team Research scientist mindset: deep thinker, creative, strong work ethic, persevering, smart a self-starter Detail oriented and capable of multitasking and delivering in fast-paced work environment As a plus: While not mandatory, a strong interest in financial markets will definitely be beneficial Participant of ACM-ICPC By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction. Copyright © 2025 WorldQuant, LLC. All Rights Reserved.WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.

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.The Infrastructure and Platform Engineering Department (IPED) in TSMC's Intelligent Manufacturing Center (IMC) is dedicated to enhancing system stability and developer productivity. As TSMC's production scale continues to expand, the core focus is on smart manufacturing through deep system integration to maintain high yield and efficiency. Within this team, you will assist in implementing new cloud architectures (K8S) and other related cloud-native technologies to achieve the goals of DevOps. General job responsibilities for this job position are: Develop and maintain cloud-native related systems based on the K8S architecture.Tune system configurations based on metrics and user feedback.Work closely with internal development teams and seek new tools that can enhance productivity.Conduct POC (proof of concept) and assist internal development teams with implementation.

About BTSE:彼特思方舟 is a specialized service provider dedicated to delivering a full spectrum of front-office and back-office support solutions, each of which are tailored to the unique needs of global financial technology firms. 彼特思方舟 is engaged by BTSE Group to offer several key positions, enabling the delivery of cutting-edge technology and tailored solutions that meet the evolving demands of the fintech industry in a competitive global market.About the Role:We are seeking a dynamic and strategic Data Product Manager to bridge the gap between product innovation and data-driven insights. This role is responsible for defining and executing a data strategy that enhances our product offerings, optimizes decision-making, and drives business growth. You will work closely with cross-functional teams—including product, engineering, data science, and analytics—to ensure that data is at the heart of our product strategy and execution.Responsibilities:Understand product values and feature details to translate them into precise data requirements.Prioritize the product-related data requests backlog to align with product strategic objectives.Address gaps in our data ecosystem by defining tracking specifications and ensuring successful implementation and launch.Comprehend the meaning of data and clearly explain its context and significance to the data team for effective analysis.Initiate data insight projects with the data team for internal sharing and continuous product improvement.Qualifications:3+ years of experiencein data, analytics, or a related roleExperience definingdata tracking / event specsand coordinating with engineering or data teamsComfortable definingdata requirements, and able to structure dashboards and metrics based on product or business needsFamiliar withtrading products and workflows(e.g. stocks, futures, or crypto), with enough hands-on exposure to understand user behavior and data needsAble tocommunicate clearlywith product, engineering, and data teamsBonus Points:Experience in the blockchain or financial technology industry.Background in data analysis or data science.Perks Benefits:Competitive salary and benefits package.Opportunity to work in a fast-paced and innovative environment.Be part of a growing and dynamic team.Make a real impact on the company's success.Various team building programs and company events.Comprehensive healthcare schemes for employees and dependants.And many more! Apply and let us tell you more!#LI-JY1

【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。