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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。

建構與優化機器學習模型: 運用多維度運動數據（如賽事數據、球員表現），開發球員薪資計算、表現預測等核心模型，並持續進行優化。 支援產品與行銷決策: 深入分析用戶行為與市場趨勢，提供數據洞察，協助產品團隊優化功能、支援行銷團隊制定精準策略。 整合生成式 AI 應用: 導入並開發生成式 AI 功能，例如自動化產出運動新聞與球員動態，豐富產品內容。 提升內部數據工作流程效率: 運用 AI 技術優化資料處理、分析與建模的流程，提升團隊整體開發效率。

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.

職類: 資料科學家,資料工程師,數據分析師／資料分析師【工作內容】需要在專案中負責發掘、分析、傳達和確認客戶需求；同時瞭解有關產品上的各種問題，並推薦問題的解決方案以實現組織的目標。1. 具備完善的溝通與簡報能力，能清楚的表達分析看到的問題與機會。 2. 深度瞭解重點客戶產業類別及使用環境、需求產品及解決方案，並能夠應用於重點客戶 日常顧問服務作業。3. 及時提供商務推動市場所需資料，以利團隊從數據中找到成長機會點。 4. 其他執行主管交辦事項。【 工作待遇 】 面議，經常性薪資4萬以上【 必要條件 】1. 良好的解決能力思維，能將觀察到的問題拆解，並有組織地思考後推論出問題背後的原因。2. 具備細心且能夠有條理、清楚表達想法與整合需求。 3. 積極主動、具責任感及高度學習動機並能夠自我管理。 4. 邏輯清晰，對數據有敏感度且有熱情。 5. 良好的耐心與自律，能勝任遠端工作模式。 6. 擅長Excel公式運用，具有撰寫良好的分析報告能力。7. 擅長應用統計、ML/DL 來建構用戶分類、異常分析等目標。8. 擅長建立數據分析系統，進行 GA 分析、設計用戶標籤。

・負責收集、清理、管理平台內外部數據，確保資料完整與正確，打造可供分析使用的數據集・監控數據質量與資料庫模型，持續優化數據處理流程・分析用戶行為（活躍、留存、付費）、市場活動成效及用戶來源渠道・應用統計、ML/DL 和生成式 AI 技術來建立使用者分類、詐欺偵測、情緒分析和其他目標的功能・以數據支持產品優化，協助設計及分析A/B測試・與其他產品開發團隊合作，了解他們的業務需求，如潛在用戶名單、用戶風險分析，制定並完成端到端分析，包括資料收集、分析、持續擴展交付和演示・使用Tableau/Power BI設計並維護BI報表，推動數據自助化・結合業界Knowhow與指標洞察，提出實際可行的解決方案

Minimum qualifications: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL), or 8 years of experience with a Master's degree. Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 12 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL). 5 years of experience in extracting and manipulating large datasets and designing ETL flows. About the jobHelp serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next. The Business Platform for Sales and Support (BPSS) team is part of Enterprise Platforms and Ecosystems (EPE) within Corporate Engineering (CorpEng), with a mission to build products for Google's internal contact center business for sales and support. We are a fast-moving, high-impact team that operates like a startup, with the resources of Google behind us. As a Data Scientist on this team, you will work closely with product and engineering teams throughout the entire development process to help build and shape next-generation GenAI products for our users.Responsibilities Define, own, and evolve product success metrics, as well as report, analyze, and forecast key product trends to make recommendations for improvement. Perform data exploration to understand user behavior and identify opportunities for improving products. Apply technical expertise in observational data analysis, modeling, and causal inference to answer product questions. Lead the design, analysis, and interpretation of product experiments to measure the causal effects of product changes. Partner with Product, Engineering, and other cross-functional teams to influence, prioritize, and support product strategy. This involves framing and solving ambiguous business problems, acting as a thought partner, influencing a wide range of product and engineering 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: Master's degree in Statistics or Economics, a related field, or equivalent practical experience. 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree. Experience with statistical data analysis such as linear models, multivariate analysis, causal inference, or sampling methods. Experience with statistical software (e.g., SQL, R, Python, MATLAB, pandas) and database languages along with Statistical Analysis, Modeling and Inference. Preferred qualifications: Experience translating analysis results into business recommendations. Experience understanding potential outcomes framework and with causal inference methods (e.g., split-testing, instrumental variables, difference-in-difference methods, fixed effects regression, panel data models, regression discontinuity, matching estimators). Experience selecting tools to solve data analysis issues. Experience articulating business questions and using data to find a solution. Knowledge of structural econometric methods. About the jobAt Google, data drives all of our decision-making. Quantitative Analysts work all across the organization to help shape Google's business and technical strategies by processing, analyzing and interpreting huge data sets. Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior. As an analyst, you do more than just crunch the numbers. You work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust Google's practices according to your findings. Identifying the problem is only half the job; you also figure out the solution. Responsibilities Interact cross-functionally with a variety of leaders and teams, and work with Engineers and Product Managers to identify opportunities for design and to assess improvements for advertising measurement products. Collaborate with teams to define questions about advertising effectiveness, incrementality assessment, the impact of privacy, user behavior, brand building, bidding etc., and develop and implement quantitative methods to answer those questions. Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct analyses that include data gathering and requirements specification, exploratory data analysis (EDA), model development, and delivery of results to business partners and executives. Build and prototype analysis pipelines iteratively to provide insights at scale. Develop knowledge of Google data structures, metrics, advocating for changes where needed for product development. 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 in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL), or 5 years work experience with a Master's degree. Preferred qualifications: Advanced degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. Experience with conceptualizing and implementing scalable data pipelines. Experience with statistical packages (e.g., R, Python, etc.) to perform forecasting, segmentation, and classification. Knowledge of basic statistics and commonly used statistical methods (e.g., hypothesis testing, regression, cohort analysis, etc.). Strong data visualization skills, including building dashboards and visualizations for business reviews and executive-level presentations. About the jobHelp serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next. Developer and Sustainability team’s mission is to apply data science to enable Geo in driving developer growth and planetary sustainability. We enable driven decision making across the Geo Makers organization (made up of Geo Developer and Geo Sustainability areas) to influence strategy, drive impact and unlock sustainable product growth.Responsibilities Lead the transformation of our self-serve analytics platform by introducing new metrics and drill downs to assist with self-serve diagnostics at scale, and driving integrations with GenAI tooling (NotebookLM, SQLMiner) to scale insight generation capabilities. Utilize technology to address new problem areas with segmentation analysis, recommender systems and GenAI applications. Build self-serve tooling and dashboarding to enable data driven decision making across the organization at scale. Collaborate on in-depth analytical projects, uncover insights and evaluate headroom to drive product enhancements which improve our developer experience. Surface insights around emerging markets (India and other APAC countries) that help teams understand users and guide global data improvement strategy. Design, execute and analyze experiments to evaluate growth levers and regional launches. 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.

Salary: Negotiation Location: Ho Chi Minh Office (Văn phòng Hồ Chí Minh) Team: Data Analytics (Phân tích dữ liệu) Application deadline: 05/12 — 31/12/2025 Job Scope The perfect candidate should have a combination of technical expertise, analytical thinking, and business acumen. You will have a crucial role in converting data into valuable insights that drive business decisions. This involves using various skills and tools to clean, analyze, and visualize data, as well as creating machine learning models and data products to support different business functions. Data Analysis: Perform detailed data analysis and interpretation to identify trends, patterns, and insights.Utilize statistical tools and techniques to extract actionable insights from large and complex datasets.Conduct ad-hoc analysis to address specific business questions and challenges. Machine Learning and Predictive Analysis Develop machine learning models to support various business functions, enhancing predictive/ prescriptive capabilities and operational efficiency. Reporting and Visualization: Develop and maintain regular PBI reports and dashboards to track key business metrics and facilitate informed decision-making.Present findings and insights to stakeholders through clear and compelling visualizations.Train support business users on building dashboards/ visualizations on their own. Collaboration: Work closely with various departments to understand their data needs, pain points and provide analytical support.Collaborate with Digital Technology and Data Engineering teams to improve data infrastructure and accessibility.Participate in cross-functional projects to drive data-driven decision-making. Strategic Insights: Provide recommendations based on data analysis to support strategic planning and decision-making.Identify opportunities for process improvements and operational efficiencies.Monitor industry trends and competitive landscape to inform business strategies. Documentation: Document all methodologies and results to ensure clarity and reproducibility of analyses. Benefit package: Attractive salary package depending on seniorityHybrid Work Policy16 days annual leave + 6 paid sick leavePVI Healthcare extraLearning Training opportunityCaring policies, supportive and employee-centric work environmentEngagement Activities

1.風險數據分析 ・蒐集並分析遊戲相關交易數據，偵測異常與高風險行為・建立可視化風險控管儀表板，提供同仁觀察及定位出風險點・建立並優化風險模型，包含詐欺偵測、異常遊戲行為分析 2.監控與報告・建立即時監控系統，追蹤玩家與交易動態，提供即時風險警示・定期產出風險控管報告，協助管理層決策 3.跨部門合作 ・支援營運、產品與客服團隊，提供數據洞察，降低業務風險・制定風險控管流程與防範措施・協助內部人員辨識風險與詐騙手法