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【關於我們 - Data Munger AI】 Data Munger 致力成為企業與實用 AI 解決方案間的最佳夥伴，從導入一路陪伴到落地。 在人人喊AI的時代下，真正為企業打造一個會持續進化的「AI 大腦」讓決策更快、流程更簡，讓人力價值最大化。 官網： https://datamunger.io/ 💼 工作職責 資料處理管道設計與開發 使用 Python 與 BigQuery SQL 為 AI 應用設計、開發及維護資料處理流程，確保機器學習模型可獲取高品質資料。ETL/ELT 工作流程構建 建立並優化 ETL/ELT 流程，確保資料自動化處理與數據一致性。RAG 系統實作 應用 RAG（檢索增強生成）技術，提升 AI 互動的準確性與上下文相關性。向量資料庫與查詢優化 優化向量資料庫（如 Pinecone、Qdrant）及 SQL/BigQuery 查詢效能，提升 AI 搜尋與回應速度。API 建構與維護 使用 Python 框架（FastAPI、Flask）建立並維護資料處理與 AI 服務 API。機器學習模型與資料管道部署 在雲端基礎架構（主要以 GCP 為主，並整合部分 AWS）上部署 ML 模型與資料管道，實踐 MLOps 原則以確保部署具備可重現性、擴展性及監控能力。跨部門協作與技術創新 與資料科學家、AI 研究人員及前端團隊協作，共同打造端對端 AI 產品，並持續導入最新技術以優化解決方案。

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. We are seeking a talented and innovative Data Scientist to join our strategic HR team. This role is instrumental in driving HR transformation through the application of AI, data analytics, and emerging technologies. The ideal candidate will possess strong AI capabilities using Python, general IT knowledge in databases, systems, and UI/dashboard prototyping; a background in computer science, information management, or a related field. The Data Scientist will function as an HR RD specialist, exploring and implementing advanced tools and methodologies to enhance HR processes and deliver substantial business impact. Responsibilities:1. AI and Data Analytics in HR: (1) Develop and implement AI models and machine learning algorithms using Python to optimize HR processes. Perform advanced data analytics, including handling big data in various formats (e.g., text data using NLP), to generate actionable insights for HR transformation. 2. Research and Development: (1) Investigate and stay current with emerging AI and intelligent tools, assessing their potential applications in the HR domain.(2) Conduct proof of concept (POC) projects to test and validate new technologies and methodologies. 3. Data Handling and Modeling: (1) Manage, pre-process, and analyze large datasets to support HR initiatives.(2) Build and validate predictive models to forecast HR metrics and enhance decision-making processes. 4. Tool Development and Prototyping:(1) Develop and prototype user interfaces and dashboards to visualize data insights and support HR decision-making.(2) Integrate various systems and databases to streamline data flow and accessibility. 5. Collaboration and Innovation: (1) Collaborate with HR and other departments to identify opportunities for AI-driven improvements.(2) Work with cross-functional teams to implement data-driven solutions that enhance employee experience and operational efficiency. 6. Strategic Contribution: (1) Provide data-driven insights and recommendations to support the strategic planning process.(2) Contribute to the development and execution of HR strategies through robust data analysis and reporting. 7. Technical Expertise: (1) Utilize Python, SQL, and other relevant tools for data analysis, AI model, and automation tool development.(2) Employ visualization tools such as Power BI, Tableau, and web technologies like React or JavaScript for dashboard development. 8. Multi-Tasking and Impact: (1) Manage multiple tasks and projects simultaneously, demonstrating an eagerness to contribute and make a positive impact.(2) Support colleagues in improving daily work processes and strategic planning. 9. Team Player:(1) Work effectively within a team, fostering a collaborative and supportive environment.

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.

About the roleWe’re looking for a Data Scientist to turn data into insights and production-ready solutions. You’ll partner with product, engineering, and business teams to frame problems, build models and analyses, and translate results into measurable impact.What you’ll do- Identify and integrate new internal or external datasets to enhance product capabilities and business insights.- Collaborate with engineering teams to support the development and deployment of scalable data products.- Conduct analytical experiments to address complex problems across different domains and industries.- Source and collect large volumes of structured and unstructured data based on client or business needs.- Develop and apply algorithms and models to extract value from big data, including error analysis and performance tuning.- Clean, validate, and transform data to ensure consistency, accuracy, and usability across pipelines.- Analyze data for trends and patterns, and translate findings into actionable insights with clear business objectives.

【關於我們】 我們是國泰產險的資料科學（DS）團隊，使命在於持續進化數據應用，創造並釋放數據價值。目前正在藉由數據上雲、數據治理與 AI 技術應用，推動由底層架構到業務應用的全端數據生態建構與 AI 轉型準備。 我們尋找認同以下團隊文化的夥伴： * 目標成果導向：重視成果並具合作互助精神 * 積極主動、持續進步：樂於學習與自我成長 * 熱愛數據、對技術充滿熱忱：積極探索與應用新技術 加入我們，一同打造高效且可擴展的數據架構，與跨部門團隊協作推動創新技術應用，提升業務決策精準度與數據價值！👀更多關於我們做的數據服務，期待您的加入，運用數據專案管理與技術整合能力，推動 AI 轉型與數據生態建構，讓數據創造最大價值！1. 九成跨域人才！國泰產險多元跨域、探索共融 打造數位數據轉型創新基地🔗https://www.bnext.com.tw/article/81887/cathay_ddt_2025012. 國泰產險推業界首創「CarTech智能車險加值服務」，數據驅動助法人車隊落實損害防阻🔗https://www.bnext.com.tw/article/81313/cathay-ins2024113. 國泰產險數位轉型新里程！AI與數據驅動加速全險種理賠、提升風控更有效阻詐2,300萬🔗https://www.bnext.com.tw/article/81460/samrtclaim_2024

We are currently hiring for （Sr.) Data Scientist (資深) 資料科學家 professionals that will take part in: What you’ll do:▸ Collaborate with product, operations, and marketing teams to define goals for data analysis and model applications.▸ Perform data cleaning, feature engineering, and exploratory data analysis (EDA).▸ Build predictive, clustering, and recommendation models, and evaluate and optimize their performance.▸ Assist in designing A/B tests, analyze experiment results, and validate strategic effectiveness.▸ Integrate multiple data sources (such as behavioral data, transactional data, and third-party tracking tools).▸ Communicate insights through data visualization and storytelling to support decision-making.▸ Work closely with Data Engineers and Analysts to optimize data pipelines and model deployment processes.▸ Research, exploration, and development of applications leveraging Large Language Models (LLMs) 歡迎對以下工作內容有興趣的 （Sr.） Data Scientist (資深)資料科學家 加入我們的大家庭！您將負責的事：▸ 與產品、營運、行銷團隊合作，定義數據分析與模型應用目標▸ 進行資料清洗、特徵工程與探索性資料分析（EDA）▸ 建立預測、分群、推薦等模型，並評估與優化其效能▸ 協助設計 A/B Test，分析實驗結果，驗證策略成效▸ 整合多元資料來源（如行為資料、交易資料、第三方追蹤工具）▸ 以視覺化與故事化方式傳達洞察，支持決策制定▸ 與 Data Engineer、Analyst 協作，優化資料流與模型部署流程▸ 研究、探索並開發運用大型語言模型（LLM）的應用

Mô tả công việcBuilding Machine Learning models using your core expertise.Collaborate with Product and Business to define the Machine Learning product, focus on Personalization and Financial Services.Collecting, cleaning, preparing data at large scale for modeling.Adding new features, exploring new approaches to keep pushing the model performance.Participating in productionizing Machine Learning models for live production.Designing, conducting A/B tests and analyzing the results for experiment insights.Building pipelines for continuously validating and updating models.Yêu cầu công việc3+ years working experience with 2 years hands-on with ML, or 2+ years with Ph.D. degree.Good understanding of mathematical foundations of Machine Learning algorithms.Have practical experience in applying Machine Learning in personalization, credit scoring or user behavior analysis.A builder. You go the extra mile to bring your prototypes to production.Strong product ownership. You take a high responsibility for what you build. You keep a high bar for product quality.Strong collaboration skills. You reach out to help other team members.Experience with credit scoring or financial service models is a plus.

1.理解研發或商務單位提出之需求，使用數據或AI方法進行分析、提出並驗證解決方法，並展示工作成果。2.持續追蹤和研究最新的AI技術和學術論文，將新知整合應用於現有系統或是提出新應用。

Minimum qualifications: Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field or equivalent practical experience. 5 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of experience with a PhD degree. Preferred qualifications: 8 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of experience with a PhD degree. Experience with data, metrics, analysis and trends with the knowledge of measurement, statistics and program evaluation. Ability to learn about Supply Chain Operations. Excellent problem-solving and business judgment skills. About the jobThe Cloud Supply Chain Data (CSCD) Data Science and Product team build productivity and data products, develop Artificial Intelligence (AI)/Machine Learning (ML)/statistical models and provide insights to help Cloud Supply Chain and Operations (CSCO) define and achieve business goals.The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide. We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.Responsibilities Develop machine learning and statistical models to detect anomalies, forecast trends, classify patterns and optimize processes in Google Cloud Supply Chain and Operations. Deliver investigative problems with guidance structuring approach and conduct exploratory data analysis, inform model design, and development. Plan and execute prioritized project work, including selecting appropriate methods and advising on opportunities to improve data infrastructure. Identify and recommend ways to improve solutions to problems by selecting better methods or tools. Identify issues with scope, data, or approach. Escalate issues to be addressed by stakeholders and communicate, present insights, and recommend actions to stakeholders. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor's degree or equivalent practical experience. 5 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data. 5 years of experience managing projects and defining project scope, goals, and deliverables. Preferred qualifications: Master’s or Ph.D. degree in a quantitative discipline (e.g., Computer Science, Statistics, Mathematics, Operations Research, etc.) 5 years of experience in a large-scale data analysis or data science setting, including abuse and fraud disciplines, with a focus on web security, harmful content moderation, and threat analysis. Experience in scripting languages (e.g., C/C++) with proficiency in programming languages (e.g., Python, Julia, etc.) and database languages like SQL. Experience with prompt engineering and fine-tuning LLMs. Proficiency in applying machine learning techniques to large datasets. About the jobTrust Safety team members are tasked with identifying and taking on the biggest problems that challenge the safety and integrity of our products. They use technical know-how, excellent problem-solving skills, user insights, and proactive communication to protect users and our partners from abuse across Google products like Search, Maps, Gmail, and Google Ads. On this team, youre a big-picture thinker and strategic team-player with a passion for doing what’s right. You work globally and cross-functionally with Google engineers and product managers to identify and fight abuse and fraud cases at Google speed - with urgency. And you take pride in knowing that every day you are working hard to promote trust in Google and ensuring the highest levels of user safety. The AI Safety Protections team within Trust and Safety develops and implements cutting-edge AI/LLM-powered solutions to ensure the safety of generative AI across Google's products. This includes safeguards for consumer products, enterprise offerings (e.g., Vertex AI), on-device applications, and foundational models (e.g., Gemini, Juno, Veo, etc.) in collaboration with Google DeepMind. We are a team of passionate data scientists and machine learning experts dedicated to mitigating risks associated with generative AI and addressing real-world safety with LLM/AI technology (e.g., imminent threat, child safety, etc.).As a member of our team, you will have the opportunity to apply the latest advancements in AI/LLM, work with teams developing cutting-edge AI technologies, and protect the world from real-world harms.This role works with sensitive content or situations and may be exposed to graphic, controversial, or upsetting topics or content.Responsibilities Develop scalable safety solutions for AI products across Google by leveraging advanced machine learning and AI techniques. Apply statistical and data science methods to examine Google's protection measures, uncover potential shortcomings, and develop actionable insights for continuous security enhancement. Drive business outcomes by crafting compelling data stories for a variety of stakeholders, including executive leadership. Develop automated data pipelines and self-service dashboards to provide timely insights at scale. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.