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1. 我們希望你能用專業的財務技能，負責和處理公司的請款追蹤及帳務管理。確保正確的金流往來、發票資訊、應收應付和日常報表追蹤。 2. 同時，我們希望你運用excel能力處理客戶的資料收集

ABOUT US Amaris Consulting is an independent technology consulting firm providing guidance and solutions to businesses. With more than 1000 clients across the globe, we have been rolling out solutions in major projects for over a decade – this is made possible by an international team of 6000 people spread across 5 continents and more than 60 countries. Our solutions focus on four different Business Lines: Information System & Digital, Telecom, Life Sciences and Engineering. We’re focused on

作為數據行銷業務專員，您會是先鋒負責Ret[AI]ling Data商務開發合作! 任務是針對核心產品與開發團隊合作開發，拓展品牌數位行銷的發展，能者多得，能在簽約後獲得BOMUS的業務獎金! 歡迎對數據數位

Job Description Memahami tujuan bisnis dan mengembangkan model yang membantu mencapainya, bersama dengan metrik untuk melacak kemajuannya Menganalisis algoritma ML yang dapat digunakan untuk memecahkan masalah tertentu Menjelajahi dan memvisualisasikan data untuk mendapatkan pemahaman tentang data Mengidentifikasi perbedaan dalam distribusi data yang dapat mempengaruhi kinerja saat menerapkan model di dunia nyata Memverifikasi kualitas data, dan/atau memastikannya melalui pembersihan data Mengaw

1. 設計/開發/維護大數據相關專案, 包含Data Warehouse管理, 負責資料建模、收集、存取與儲存等功能 2. 建立 Batch/Streaming ETL pipeline，並確保數據品質與正確性 4. 維護雲端大數據架構及服務 5. 理解使用者

Job Responsibilities : A. Entering data from source documents within time limits B. Compiling, verifying accuracy and sorting information to prepare source data for computer entries. C. Reviewing data for deficiencies or errors, correcting any incompatibilities and checking outputs.

【工作內容】 與產品團隊和前後端工程團隊合作，確保資料品質與產出 創建與維護Data Infrastructure Data Pipeline & ETL/ELT Data Product開發與維護

#About the Team Fazz’s Data Engineering teams are responsible for creating and maintaining the infrastructure that runs the company’s data pipeline, and optimizing the flow and collection of data for the critical business analytics and AI/data-driven solutions. The success of the team relies on the high engineering standard and the adoption of cutting-edge technology that empowers the organization to be agile. Data engineering forms the foundation to ensure that precious data

1. 數據資料前處理（包含數據清洗、特徵工程） 2. 機器學習、深度學習或其他相關演算法開發 3. 數據與機器學習模型可視化處理 4. 依專案需求，參與系統架構流程規劃 5. 協同前端、後端

Build dashboards, self-service tools, and reports to analyze and present data associated with business operations and Marketing performance to support key business stakeholders to make data-driven decisions in the organization. Consulting and problem-solving mindset: Ability to work with ambiguity and uncertainty, digest business problems, propose and implement analytical solutions to derive value and outcomes. Support and manage data requests from business stakeholders – can understand business