Cake 找工作

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。

公司介紹： 我們的客戶是一家領先的金融科技公司，致力於通過數位、數據和技術推動整體轉型。公司正在積極打造數據驅動文化，以成為提供卓越金融服務的科技公司為目標。公司環境開放創新，鼓勵員工發揮創造力，實現職業理想。 JD: 1. 機器學習、深度學習或統計分析模型專案開發 2. 配合數據技術發展目標，研究與實作可落地應用之新興數據模型技術 3. 協助數據轉型，規劃end-to-end的數據應用解決方案 4. 當負責之數據服務被設定為""不能中斷""之服務等級，則需配合維運團隊於非上班時段on call以便即時處理問題，確保服務穩定。

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.

・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

🏦🌐臺灣的大型金融控股公司🏛️🌐🏦參與集團 新技術導入 AI 技術開發與應用 與 商務等數據洞察與業務應用探索 AI 技術開發與應用：負責大語言模型調優技術開發，因應不同子公司業務需求，設計模型應用方式和落地規劃。 數據洞察與業務應用：分析結構/非結構化數據，包含數位軌跡資料、金控資料庫、外部公開資訊等，拓展數據科學應用，發掘潛在商機並提出符合業務決策建議。 具數據探索、處理分析能力，能獨立推動運作專案。 思慮邏輯清晰，有良好溝通技能及創新精神。

知名資安軟體公司裡面的AI創新研發部門，正在找尋具備軟體開發思維的Data Scientist(NLP)，將探索如何在網路安全領域應用實用或最新的先進演算法。不僅要符合公司的戰略，還要為客戶帶來價值！

1. 洞察公司營銷/工廠運維的數據，並應用數據挖掘、機器/深度學習、最佳化等等技術，優化產品品質、提升生產效率減少資源的耗用、提升設備的妥善率，並找到問題的根因與最適的生產操控作業。2. 以智慧製造的策略發展，應用集團內各工廠的生產數據與領域專家合作，制定生產製造所產生的問題，處理相關數據以符合製程的運作，並應用相關的演算法，建立線上即時預測或分析模型，協助工廠解決生產問題的痛點。 3. 協助商業營運銷售活動的分析，開發應用相關演算法模型進行分析與預測，提升獲利與企業競爭力。4. 依照環境的現況，設計出最佳的解決方案，模型部署在（On-prem / Cloud / Edge），並做視覺化呈現或告警通知給予使用者最適的業務運作協助。管理線上模型的生命週期，研究與開發相關演算法，保持模型的預測的效用與運作效率。 5. 參與智慧工廠、數位分身（Digital Twin）等專案，持續追蹤並導入新興 AI 技術（如 Generative AI、多模態模型），提升系統效能與應用深度。 6. 撰寫技術文件與專案成果報告，協助跨部門溝通與知識傳承

Minimum qualifications: Master's degree in Statistics, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field. 3 years of experience with Machine Learning and Statistical modeling, especially in anomaly detection and classification models. Preferred qualifications:2 years of experience in using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis. Knowledge of data metrics, analysis, and trends, as well as measurement, statistics, and program evaluation.Excellent business judgment and a problem-solving mindset, with the ability to apply both statistical methods and flexible approaches to complex issues.About the jobIn this role, your mission is to build productivity and data products, develop AI/ML/statistical models and provide prescriptive insights to help Cloud Supply Chain and Operations (CSCO) define and achieve business goals. You will help make Google Cloud supply chain and Data Centers exceptional by enabling data-informed decision making and product innovation.Areas of Focus:Through applied modeling, you will pursue high-impact forecasting, anomaly detection, GenAI, automation and statistical modeling opportunities.Through prescriptive insights, you will inform supply-chain, operations and product decisions that drive long-term strategies or 8+ figure $ impact. Through product management, you will help CSCO achieve business goals through data, AI and ecosystem products.Through measured work, you will enable data center productivity measurement and improvements.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 difficult investigative problems with initial guidance structuring approach and conduct exploratory data analyses, inform model design, and development. Plan and execute prioritized project work, including selecting appropriate methods and advice on opportunities to improve data infrastructure. Identify and recommend ways to improve solutions to problems via selecting better methods/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.

數據驅動決策與營運最佳化是上洋邁向智慧營運的重要一步。我們正在尋找一位對資料分析與商業洞察具備熱情與專業的資料科學家（Data Scientist）。此角色需主動與產品、營運、業務與工程團隊密切合作，快速理解商業情境與問題，將資料轉化為可行的洞察與決策建議。你將透過資料分析、統計建模與機器學習方法，協助公司發現機會、優化流程，並推動以數據為核心的產品與營運策略。身為資料科學家，你/妳將會執行以下內容：1.主動與產品、營運與業務團隊溝通需求，快速理解商業邏輯與問題背景，將業務問題轉化為可分析的資料問題。2.進行探索式資料分析（EDA），找出資料中的模式、趨勢與異常，並提供具體的商業洞察。用於但不限於預測、分類、推薦或營運最佳化。3.在必要情境下具備基本資料處理與資料管道能力，能獨立處理資料取得、清理與轉換，而不完全依賴資料工程師。4.使用視覺化工具（如 Superset、Metabase）或 Notebook 報告，將分析結果清楚呈現給非技術團隊。5.持續評估與導入 AI 與資料分析工具（如 LLM、AI coding assistants），提升分析效率與洞察速度。6.優化資料結構與資料品質，確保分析所需資料可靠且可用。