轉職熱搜工作

職缺亮點 • 參與AI與金融科技防詐專案，打造智慧金融風險管理機制 • 與跨部門合作推動金融防詐與風控策略 • 可接觸最新防詐技術與國際金融科技趨勢 隨著詐騙型態日益複雜，我們持續導入AI與數據分析技術強化金融防詐能力。誠摯邀請對金融科技、AI應用與風險管理有興趣的人才加入，共同守護金融安全。 工作內容 1. 參與AI數據與創新科技應用於金融防詐與風險管理專案。 2. 協助建立與優化異常交易監控與風險判斷機制。 3. 配合主管機關辦理防詐政策及相關專案合作（資料提供、專案交流等）。 4. 規劃並推動跨部門防詐專案，協助落實風險管理措施。 5. 研究並追蹤國內外防詐技術與金融科技發展趨勢，提出創新應用建議。

工作內容： ＜About the job＞： We‘re seeking AI/ML enthusiasts with experience and skills in working and are passionate about extending AI/ML expertise. The Data Science & AI team of headquarter IT is developing the frontier and practical analytic technologies that enhance the data value. As the AI/ML engineer, you‘ll join the AI/Big Data Analytics program/projects of headquarter IT and assist in building the model/algorithm to empower data-driven & analytics-driven for driving business value from data insights in this world-class company (Fortune Global 500, 22nd). ＜Job Type Option：＞ *Type1: AI/ML Engineer (Engineering-Oriented) (1) Use Machine Learning/Deeping Learning/Analytical techniques to build models for internal different scenarios and requirements. (2) Building the model lifecycle from data exploration to feature engineering to model evaluation and validity analysis capabilities. (3) Execute efficient, scalable, automated processes for model development, model validation, and model implementation (4) Deploy the model to production and maintain/optimize the models by MLOps. (5) Experience in Azure Data Lake, Azure Databricks, and Azure Data Factory is preferred. (6) Experience in AWS SageMaker is preferred. *Type2: NLP AI Engineer (1) Focused on NLP Algorithm/Machine Learning & Deeping Learning for Text. (2) Develop the Algorithm of NLP(Natural Language Processing)/ Computational Linguistics/Text Mining/Topic Modeling (3) Join the project to build the end-to-end NLP systems, from understanding the requirements to selecting training datasets to model, evaluate, and deliver/deploy NLP models. (4) Fine-tune LLMs and optimize and resolve issues related to LLM usage in production scenarios, enhancing reliability, accuracy, and performance. *Type3: AI/ML Engineer (Analytics-Oriented) (1)Use Machine Learning/Deeping Learning/Analytical techniques to build models for internal different scenarios and requirements. (2)Build the model lifecycle, e.g., from data exploration to feature engineering to model evaluation and validity analysis capabilities. (3)Execute efficient, scalable, automated processes for model development, model validation, and model implementation. (4)Apply quantitative methods including but not limited to above tasks to solve business problems. (5)Being passionate and patient about working with complex data ＜Skills＞ ．Type1 & 3 : AI/ML Engineer(Engineering-Oriented & Analytics-Oriented) (1)Familiarity with any one of Machine Learning, Statistical Modeling, Deep Learning (Nature Language/Image/Time Series) model/algorithm building of the practical application in the industry. (2) Being familiar with Python Libraries, e.g., Numpy, Pandas, Scikit-Learn, SciPy, Matplotlib, etc. (3)(For Engineering-Oriented) Knowledge of Big Data with Machine Learning/Statistical modeling related technologies such as Spark MLlib or PySpark or SparkR/SparklyR. (4)(For Analytics-Oriented) Knowledge of Deep Learning Framework such as TensorFlow/Caffe/Pytorch/Keras. ．Type 2: NLP AI Engineer (1) Experience with text mining algorithms such as word segmentation, POS tagging, named entity recognition...etc. (2) Experience in algorithms and libraries of NLP(Natural Language Processing), especially in machine learning techniques applied to NLP, such as Text mining, Text classification, Information Extraction, Keyword Tagging, and content discovery. (3) Familiar with one general-purpose programming language (e.g., Python, Java, C/C++) (4) Experience manipulating and integrating unstructured, semi-structured, and structured data. (5) Excellent knowledge and demonstrable experience using open-source NLP packages such as NLTK, Word2Vec, Standford CoreNLP, SpaCy, and Gensim. (6) Knowledge of Open source LLMs, such as BERT, BLoom, LLaMA..., etc., and NLP frameworks, like Hugging Face Transformers, PyTorch /JAX

本職位將負責 Web 及 App 的使用者體驗設計、營運數據分析與跨部門專案協調。如果你具備良好的邏輯思考、跨團隊溝通能力，並喜歡從數據中發現洞察、優化服務，歡迎加入我們！ ☆工作內容☆ 1. 服務流程規劃、撰寫專案企劃文案、視覺圖稿設計與產品規格文件 2. 觀察使用者行為與數據，進行大數據分析以提供服務優化建議 3. 協助營運端分析市場數據（如 App Store / Google Play 等平台數據及評分） 4. 可獨立作業並針對各業務進行跨部門專案協調專案溝通、合作 5. 即時處理反映的問題，包含問題確認及進度追蹤 6. 處理主管交辦事務 ☆基本條件☆ 1. 熟悉 office 操作（精通Excel、Word、PPT） 2. 具備軟體開發、數位媒體、內容平台領域知識等尤佳 3. App / Ｗeb 開發經驗 4. 具基本系統概念（API、資料流、系統串接） ☆薪資福利 1. 具備10年以上相關工作經驗者：將依資歷敘薪，經常性薪資最高可達 40K 2. 年終獎金另計 3. 另享福委會福利金

1.AI模型的設計、開發、測試與優化。 2.生成式AI應用(如LLM的應用開發)。 3.數據處理與分析(如數據清洗、特徵工程及標註管理)。 4.系統整合、部署與優化。 5.AI技術研究與導入專案應用評估。 ※工作地點可選擇 台北市信義區 或 台中市西區 (將於面談時雙方議定)

Job Summary 此職位為偏軟體與資料工程導向的工程師角色，主要負責將實際使用者 (User) 需求轉化為可落地的資料流程、後端服務與視覺化應用。 工作重心聚焦於資料處理、系統整合、效能與穩定性，並透過與使用單位的密切溝通，持續優化系統與報表，確保資料能被正確且有效地應用於實際業務場景。 Key Responsibilities - 與內部使用者（如工廠、營運或相關單位）溝通需求，釐清實際使用情境，並將需求轉化為具體的系統設計、資料流程或報表規格 - 使用 SQL、Python 進行資料處理、清洗與轉換，設計與維護穩定的資料管線（ETL / Pipeline） - 開發與維護後端服務或 API，支援資料存取、系統整合與應用功能 - 規劃並開發 BI / Dashboard 視覺化報表（如 Tableau），確保資料正確性、可讀性與實際可用性 - 與其他工程師、IT 或跨部門團隊合作，進行系統串接、資料整合與流程優化 - 針對資料量成長或使用情境變化，進行效能調整、架構優化與問題排查 - 持續關注資料品質與系統穩定性，主動發現並改善影響使用者體驗的問題 ※ 本職位重視將資料與系統「做穩、做對、做給人用」，而非以模型或演算法為主要解決手段。

1. 資料倉儲管理與數據中心建置。 2. 根據市場與客戶所需, 提供數據分析結果。 3. 針對需求可提出解決方案與技術可行性評估 。 4. 營運上相關數據分析, 如會員行為模式分析,提出分群描述及預測模型。 5. 撰寫遊戲機率模組演算程式。 6. 熟悉數據管理、可視化及產出報告。

＜About the job＞： The Data Science & AI team of headquarter IT is developing the frontier and practical analytic technologies that enhance the data value. As the data scientist, you‘ll join the AI/Big Data Analytics program/projects related to management topics, including Commercial/Industrial Engineering/Supply Chain/Financial Performance/Operation...etc., to build the model or algorithm to empower data-driven & analytics-driven for driving business value from data insights in this world-class company (Fortune Global 500, 22nd). ＜Job Description＞： ．Design, implement and refine advanced Statistical Modeling/Machine Learning/Deep Learning/Numerical Simulation/Optimization Algorithm Models(at least one of the fields) ．Ensure alignment of modeling initiatives with the requirement goal defined by key stakeholders and company objectives and identify new hypotheses for model improvements. ．Executing big data analysis and predictive analytics projects include feature engineering, model building, algorithm development, etc. ．Works closely with a team of data system analysts, business data analysts, data engineers, data platform architects, etc. ．Collaborate effectively with team members, whether leading tasks or supporting initiatives led by others. ．Self-motivated, Result-oriented, and interested in applying quantitative methods to solving business and engineering problems. ＜Skills＞ ．Experience with any one of Machine Learning, Statistical Modeling, Deep Learning(Nature Language/Image), Econometric Modeling, Optimization Algorithm(OR), Numerical Simulation..., etc., model/algorithm building of the practical application in the industry. ．Familiarity with programming languages like Python or R, or Java. (Good programming skills in Python is a plus). ．Advanced ability to perform Exploratory Data Analysis and working knowledge of statistics. ．Ability to visualize data in the most effective way possible for a given task, especially visualize models and results and debug and troubleshoot code and models. ．Big on finding the many insights based on the data and being passionate and patient about working with complex data.

1 負責 Service Team 的人員與流程管理 2 負責 Service Team 整體服務品質的控制 3 負責所有客戶訂閱之服務的設定，包含服務的上線、驗收測試、異動、優化、調較與終止 4 負責所有客戶訂閱之服務的故障排除，包含對上游的支援請求與進度追蹤 5 負責所有客戶訂閱之服務的例行檢查 6 處理工單與維護工單系統 7 回應並執行或轉出客戶的服務請求 8 產出客戶所需之定期報告並舉行客戶例行會議

The Biostatistician is responsible for all the tasks of statistical analysis in clinical studies including the statistical analysis plan, statistical report, analysis datasets, TFLs output, and the corresponding SAS programming. Supervise the programmer to complete the production of datasets and analysis outputs. Oversee the progress of data management and statistical analysis for projects. Works under the supervisor of the director of the technical department to ensure the quality of statistical analysis and all the tasks that are delivered on time and within the scope and also provides statistical advice to sponsor and project team.

1.資料處理與分析能力 擅長從多元來源蒐集、清理與格式化資料，熟悉統計方法與工具，具獨立分析與解決問題的能力。 2.工具與平台操作 熟悉 Excel、Power BI、Python、PowerPoint..等工具，了解數據平台架構，具 MySQL 操作經驗，並使用過至少一款 BI 工具（如 Tableau、Looker Studio 等）。 3.報告製作與視覺化 能使用圖表與儀表板呈現分析結果，撰寫報告支援決策，具簡報製作、圖表排版與美編設計能力。 4.跨部門合作與專案推動 能與業務、行銷、產品等部門溝通協作，釐清需求並提供數據支援，具簡報表達與專案執行能力。 5.具統計相關背景或實務經驗者優先。 6.能配合主管交辦事項。