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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.

Minimum qualifications: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 2 years of experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL) (or experience with a Master's degree). Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 3 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL). 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. To accelerate the growth and market leadership of Enterprise Buying Platforms (DV360 and SA360) by answering critical business questions and delivering actionable, data-driven insights that inform product and commercial strategy. The Enterprise Platform Data Science Team provides quantitative support, market understanding and a strategic perspective to our partners throughout the organization, in close collaboration with the Ads and Commerce Finance team.Responsibilities Execute defined, moderately difficult investigative tasks under guidance from the manager or executive team member/team lead. For straightforward problems, execute end-to-end analysis with minimal guidance. Manage workload to reflect the priorities set by the team, work towards a timeline, and communicate slippage. Select appropriate approaches from clear options to address technical challenges under some guidance from managers or executive team members. Plan out analyses (as opposed to trial and error approach). Break down broader tasks into components and anticipate complexities/blockers. 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.

1. Utilize advanced algorithms and data mining techniques to build personalized recommendation systems, optimizing product and service recommendations to enhance user experience and improve business conversion rates.2. Conduct precise analysis of probability distributions in casino games, develop and validate mathematical models to ensure game fairness and risk control, supporting compliance operations and decision-making.3. Continuously explore and implement various applications of LLMs in business, from natural language processing to intelligent customer service and content generation, driving enterprises toward intelligent transformation.4. Work closely with various business units, leveraging data analysis and visualization tools to promote a data-driven decision-making culture, helping departments uncover insights from data and develop effective strategies.

Minimum qualifications: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 5 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. Experience in product analytics within payments, e-commerce, or financial services. Ability to manage and organize work sprints for themselves and a team of analysts. 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. As the key analyst on Forms of Payments (FOPs) and Business-to-Consumer (B2C) analytics, you will shape Payments products and solutions, helping our leaders make data-driven decisions. You will lead a critical part of Payments that focuses on acquiring the usage of nearly one billion users with FOPs across all Google Surfaces. You will drive analytics for FOPs launches globally, improving cards and non cards types, driving transaction performance, capturing the Quality and Value from FOPd users, as well as managing FOPs Risk and Compliance. You will also play an important role in our interactions on B2C analytics with Play and You Tube to improve Buyflows, Purchase Readiness, Conversion and UI on these critical Google products.Responsibilities Shape the future of Google Payments by leveraging data and analytics to drive decisions, influence strategy, and create business impact across the organization. Identify and solve ambiguous problems, transforming data into insights that influence leadership decisions. Lead projects that align with the organizational strategy, deliver insights that help business decisions. Contribute to the development and alignment of team Objectives and Key Results (OKRs) and analytics strategy to ensure they support the product and business goals across the Payments organization. Collaborate cross-functionally with product, engineering, and operations teams to define key metrics and support data-driven decision-making. 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.

Responsibilities Lead the design and development of end-to-end data science projects, from business problem understanding to model deployment and monitoring.Collaborate with domain experts and cross-functional teams to translate business goals into goal-driven autonomous agent workflows.Design and implement robust RAG (Retrieval-Augmented Generation) pipelines to enhance the performance of large language model (LLM) applications.Prototype and deploy multi-agent LLM systems for planning, reasoning, and task orchestration. Build and deploy machine learning models for use cases such as recommendation systems, NLP, time-series forecasting, and computer vision.

Minimum qualifications: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL) (or 2 years of work experience with a Master's degree). Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 5 years of experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL). Experience with developing one or more deep learning models for business impact, and experience debugging throughput and latency issues in AI. Experience managing large-scale data transformation pipelines for batch inference of ML models. 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. In this role, you will partner with teams across the company to apply Google’s best Data Science techniques to Google’s biggest enterprise opportunities. You will partner with Research, Core Enterprise ML and Machine Learning (ML) Infrastructure teams to build solutions for the enterprise.The Googler Technology and Engineering (GTE) Data Science team's mission is to transform Google Enterprise business operations, supply chain, IT support and internal tooling with Artificial Intelligence (AI) and advanced analytics, enable operations and product teams to succeed in their advanced analytics projects through the use of differing engagement models, ranging from consulting to productionizing and deploying models. Build cross-functional services for use across Corp Engineering, and educate product teams on advanced analytics and ML.Responsibilities Define and report Key Performance Indicators and launch impact as part of regular business reviews with the cross-functional and cross-organizational leadership team. Work with PM, User Experience (UX), and Engineering to contribute to metric-backed annual OKR setting. Come up with hypothesis to enhance performance of AI products on offline and online metrics through research on techniques around prompt engineering, RAG, supervised finetuning, in-context learning, dataset augmentation, tool-calling efficacy, planning capabilities and feedback loop with reinforcement learning. Design and develop ML strategies for data enrichment such as autoencoder based latent variables, complex heuristics, etc. Evolve variance reduction and simulation strategies to increase reliability of experiments with small sample sizes. Convert business problems into unsupervised and supervised ML modeling problems, build these model prototypes from scratch to justify business impact hypothesis. 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. 2 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL) (or work experience with a Master's degree). Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 3 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL). Understanding of digital advertising measurement concepts, including attribution modeling, incrementality testing, and media mix modeling (MMM). Excellent communication and presentation skills with the ability to influence stakeholders. 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.Responsibilities Execute defined, moderately difficult investigative tasks under guidance from the manager or executive team member/TL. Execute end-to-end analysis with minimal guidance. Manage workload to reflect the priorities set by the team, work towards a timeline, and communicate slippage. Handle data communication, limits, and importance. Collaborate with Product Managers, Engineers, and Research Scientists to define and track key performance indicators (KPIs) for Google Ads measurement products. Select appropriate approaches from clear options to address technical challenges under guidance from managers or executive team members.  Conduct in-depth analysis of large datasets to identify trends, patterns, and insights that inform product strategy and development. Communicate data and analysis in a clear and concise manner to various stakeholders, including product leadership, engineering teams, and business partners. 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. 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL), or 2 years work experience with a Master's degree. Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. Experience with Google Ads products and technologies. Familiarity with privacy-preserving technologies and data regulations (e.g., GDPR, CCPA). Knowledge of machine learning techniques and their applications in advertising. Understanding of digital advertising measurement concepts, including attribution modeling, incrementality testing, and Media Mix Modeling (MMM). 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.Responsibilities Execute defined, moderately difficult analytical tasks under guidance from the manager or team member/team lead. For straightforward problems, execute end-to-end analysis with minimal guidance. Collaborate with Product Managers, Engineers, and Research Scientists to define and track key performance indicators (KPIs) for Google Ads measurement products.  Communicate complex data and analysis in a clear and concise manner to various stakeholders, including product leadership, engineering teams, and business partners. Conduct in-depth analysis of large datasets to identify trends, patterns, and insights that inform product strategy and 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.