轉職熱搜工作

1. 資料倉儲：SQL SERVER資料庫倉儲、規劃、管理和維運。 2. 資料處理：結構與非結構資料清理與整合，設計並維護 ETL 流程，確保分析資料處理與應用效能。 3. 資料治理：資料庫權限規劃及管理、資料綱要與資料字典維護。 4. 資料自動化：因應業務需求支援各類型來源資料串接、資料處理，完善資料倉儲。 5. 資料排程：SQL SERVER、AIRFLOW資料排程。 6. 資料視覺：Dashboard開發，分析銀行營運資料中的趨勢、異常值和模式。 1. Data Warehousing: Design, planning, management, and maintenance of SQL Server data warehouses. 2. Data Processing: Cleanse and integrate structured and unstructured data; design and maintain ETL pipelines to ensure data processing efficiency and analytical performance. 3. Data Governance: Plan and manage database access controls; maintain data schemas and data dictionaries. 4. Data Automation: Support integration and processing of data from various source systems based on business needs to enhance the data warehouse. 5. Data Scheduling: Manage data scheduling using SQL Server and Airflow. 6. Data Visualization: Develop dashboards to analyze trends, anomalies, and patterns in banking operational data.

1.客戶體驗規畫師：以客戶角度經營數位理財行銷平台 2.市場趨勢洞察家：追蹤數位金融趨勢，掌握市場與同業動態 3.打造品牌吸引力：用創意及幽默感，進行財管商品行銷規劃 4.樂於用數字說故事：分析成效數據，從數據中找出優化秘訣 1. Customer Experience Planner: Manage digital wealth management marketing platforms from a customer-centric perspective. 2. Market Trend Analyst: Monitor digital finance trends and track market and competitor developments. 3. Brand Engagement Builder: Plan wealth management product marketing through creativity and a sense of humor to enhance brand appeal. 4. Data-Driven Storyteller: Analyze performance data and identify optimization opportunities based on insights.

1.開發與維護公司車隊系統應用，協助客戶解決車隊管理上的需求與問題。 2.車隊管理系統設計、測試、開發、導入與維運 3.車載裝置對接與測試 4.客製功能規劃 5.主管臨時交辦項目執行

【為什麼你要加入中租實習生行列?】 -師父引進門：實習過程有專門Mentor指導，不怕求助無門。 -工欲善其事：完善的電腦設備及環境，滿足你在開發學習上需要的所有資源。 -制度化開發：帶你了解國際級規模企業的作業制度，建立良好開發習慣。 -近朱者則赤：跟著優秀的團隊一起學習成長，耳濡目染，習慣卓越。 -贏在起跑點：表現優良者，畢業後有優先轉正機會，及早獲得加入大型企業門票。 【實習期間】 - 2026/07至2027/06。 - 每週一至五排班至少3天。 【技能要求】 1.曾經學習過一種資料庫，例如MSSQL、PostgreSQL、MySQL或Oracle資料庫等。 2.曾經學習過Python程式設計或其他程式語言。 【工作內容】 - 與AI應用工程師合作：進行各種AI Agent與Agent Skills設計，整合AI常見技術如RAG、Fine tunning，讓大語言模型編排各類工具執行任務，促進各事業單位運用生成式AI技術降本增效。 - 與微服務工程師合作：進行Python API開發、K8s CI/CD、共用服務開發維運、與.NET微服務整合、監控告警、API管理等，為應用系統創造最佳品質。 - 與數據工程/分析師合作：進行資料導出、資料導入、資料清理、資料轉換作業、Data Pipeline開發、資料特徵標記，結合Text-to-SQL技術讓AI挖掘數據價值。 ※歡迎大學四年級在校生或碩士班在校生應徵。 【學習及發展】 1.在本職務中可以熟悉了解大型企業IT團隊運作模式並累積實戰經驗。 2.透過與AI應用工程師的合作，可以學習大型企業如何與生成式AI技術接軌並投入實際營運產生效益。 3.透過與微服務工程師的合作，可以學習應用系統如何藉由容器化平台與微服務生態系，建構高度自動化之高品質資訊服務。 4.透過與與數據工程/分析師的合作，可以學習資料倉儲及資料市場的開發過程，及瞭解大數據平台的維運作業工作內容，及瞭解企業內各單位數據應用的場景。

1.銷售報表製作、文書資料彙整處理 2.細心、耐心、具責任感，能夠按照SOP流程，在時間內完成工作 3.擅長excel 公式尤佳，須具備邏輯分析能力 4.主管交辦行政事務 5.可配合輪班輪休

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.

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

1.數據蒐集與清理 ・建立並維護電商平台(蝦皮、momo、蝦皮廣告等)的數據收集流程 ・撰寫爬蟲或使用API,蒐集商品、價格、銷量、評價等數據 2.數據分析與報表 ·建立銷售、流量、關鍵字、競品比較等分析模型 ・使用 BI L具(Power BI、TableauㆍGoogle Data Studio)製作可視化報表 ・追蹤並分析行銷活動(廣告投放、折扣 )的成效

＜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.

主要協助公司進行營運流程的數據化與資料庫建置。你需要處理來自不同合作單位的繁雜資訊，確保數據的精確性以支援公司決策。 1.營運資訊搜集與整合： 針對專案需求，向外部合作夥伴（如飯店、車隊、各類供應商等）進行規格參數、營運數據之搜集與彙整。 2.資料庫維護與數據清洗： 負責原始數據的除錯、清洗、分類與標準化，將非結構化資訊轉化為系統可用的標準格式，並定期維護資料庫更新。 3.問卷工具管理與執行： 設計資訊收集表單（如 Google Form / SurveyCake），並負責後續的發放、進度追蹤、催收以及回覆內容的邏輯檢核。 4.報表製作與基礎分析： 協助將收集之數據產出統計報表，分析資源使用效率、成本結構或其他營運指標。 5.其他主管交辦事項： 協助部門行政事務及跨部門數據支援。