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Responsibilities Data Engineer 負責根據分析需求進行資料建模(data modeling)，並建立視覺化平台和資料治理 機制(data governance)，以幫助公司團隊使用這些資料：在產品內提供資料分析功能、在公司團隊內使用資料幫助商業決策等。 你的

創造驚豔的服務、為大眾帶來感動，這就是我們的出發點。 #因應疫情暫停海外介紹，待開放後重新招募，歡迎收藏職缺哦～ 【工作內容】 1. 深度學習相關技術之研究開發與實用化 2. 根據顧客的需

We are looking for a highly knowledgeable and enthusiastic machine learning engineer to help solve complex problems across a variety of audio processing projects. You will be both creating new solutions and evaluating existing machine learning (ML) processes, as well as performing statistical analysis to create and analyse large data sets. To ensure success as a machine learning engineer, you should be able to demonstrate solid data science knowledge and experience in a related ML role, as well

1. 行銷議題分析與行銷解決方案之建議，提供行銷數據分析報告 2. 數據分析、挖掘、建模、模式評估等相關工作，並進行模型評估 3. 與使用者及開發人員合作，定義 Report 及 Business Intelligence 需求及規格，參與

Get data from both internal and external sources via API or crawlers. Perform data analysis to help marketing/business teams to answer business/operational questions. Build and optimize models for business decision making. Interpret trends or patterns from complex data sets by using statistical and visualization tools. Conduct data analysis reports to illustrate/visualize the results and insight. Build analytics tools that utilize the data pipeline to provide insights to customer needs

Infocast is looking for a data engineer to help optimize, expand, test, and maintain the data pipeline architecture across all of our databases and for our upcoming products. You will be working closely with our software engineers and data scientist to understand and implement database requirements, troubleshoot issues, and improve data reliability and quality. The ideal candidate should have a solid understanding (both theoretical and practical) of machine learning techniques, and be comfortabl

- We are looking for experienced Machine Learning/Deep Learning engineers. - This is a technical role, and it requires a high willingness to learn state-of-the-art AI techniques and a skill to apply AI techniques to business applications/processes. - Participate in the engineering life-cycle, including writing production code, conducting code reviews and deploy machine learning solutions into production. - You’re not just looking for a job, you’re looking for an innovative