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【2024 最新】新加坡薪水大評比：最高薪工作、受歡迎工作
knowledge of OM, IE, IT, or related field is required. 2. Having semiconductor processes knowledge is preferred. Fluent in Mandarin and English. 3. An enthusiastic and dedicated individual with the capability to motivate and lead using a team approach. [AICS] Machine Learning Engineer (Singapore) 華碩 ASUS 經常薪資 NT$4萬 1. Bachelor’s Degree in computer science or related field with at least 3 years of relevant experience. 2. Understanding of data structures, data modeling, and software
想進入半導體業工作嗎？竹科、南科半導體公司徵才中！
美等地皆有分公司。 威盛電子的徵才職缺 招募職缺 薪資待遇 工作地點 機構工程師 32K ~ 100K TWD / 月 新店 Machine Learning 軟體程式設計師 40K ~ 100K TWD / 月 新店 華邦電子 華邦電子成立於 1987 年，是記憶體 IC 設計、製造與銷售
Fintech 金融科技新趨勢：Fintech 產業、應用及工作一次看！
軟體開發人員（Software Developer） ：精通多種程式語言和相關框架，能夠開發和維護 Fintech 產品和平台。 機器學習專家（Machine Learning Expert） ：熟悉各種機器學習算法與模型，能夠應用於預測和自動化系統。 數據庫架構師（Database Architect） ：設計與
那些新創教我的事 VII「 與公司一起快速成長，是最棒的人生經驗 」－ 鄭淙勻 (Fugle 全棧工程師)
服務自主、有想法的投資人。Fugle 開發一站式的股票研究平台，用戶可以自行建置投資組合，機器學習 (Machine Learning) 的資訊系統亦能預測用戶需要的資訊，從新聞、研究報告、產業上下游相關性、籌碼面、技術面等
20 Computer Skills to Write in Your CV [w/ Examples & Writing Tips]
Figma Procreate Enterprise Systems Payment processing Automated billing systems Salesforce Oracle Netsuite SAP Software Skills Java SQL JavaScript C++ Python Hardware Skills System administration Network configuration Software installation Vendor management Cloud management Advanced Computer Skills Skills Web development Open-source Machine learning Debugging Cybersecurity Data Visualization Tableau Qlikview Microsoft Power BI Datawrapper Sisense Collaboration Tools Asana CodingTeam Slack Trello Monday.com Search Engine Optimization Google Analytics Ahrefs SEO writing Google Keyword Planner Google Search Console Advertising Google Analytics Google Ads
Ketahui 4 Perbedaan Data Analyst dan Data Scientist!
menggunakan Excel Meneliti, mengembangkan, merencanakan, dan mengimplementasikan algoritma prediktif untuk mengidentifikasi tren yang akan datang Membuat laporan tabel dan visualisasi dasbor dengan software business intelligence untuk berbagi temuan dan rekomendasi dengan tim internal Melakukan analisis statistik menggunakan algoritma pembelajaran mesin ( Machine Learning ) seperti natural language processing , regresi logistik, KNN, dll. Berkomunikasi dengan business users untuk memahami proses bisnis dan memberikan wawasan yang dapat ditindaklanjuti untuk menginformasikan keputusan bisnis dengan lebih baik Membangun dan melatih pemodelan machine learnin g dengan menggunakan
