软体设计工程师
商业银行
台北市
面议
关键能力
深度學習機器學習文字探勘GBDT、協同過濾、LSTM
工作职责
1. Responsible for the use of machine learning and deep learning to develop models and apply them to financial scenarios
2. Responsible for the pre-processing and feature engineering of model development data
3. Cooperate with IT/AI deployment engineers to provide services for the launch of machine learning models
希望具備推薦算法、graph algorithms、異常偵測等機器學習建模經驗
EX:
Graph Theory應用範例:以graph方式儲存&運算客戶數據，並找出潛在關聯等
異常偵測應用範例: 異常金流偵測、異常交易、異常登出入軌跡等
2. Responsible for the pre-processing and feature engineering of model development data
3. Cooperate with IT/AI deployment engineers to provide services for the launch of machine learning models
希望具備推薦算法、graph algorithms、異常偵測等機器學習建模經驗
EX:
Graph Theory應用範例:以graph方式儲存&運算客戶數據，並找出潛在關聯等
異常偵測應用範例: 異常金流偵測、異常交易、異常登出入軌跡等
理想人选
1. Graduated from graduate school (inclusive), with more than 3 years of practical experience in machine learning or deep learning modeling
2. Have a solid data processing and data analysis experience for more than 2 years
3. Familiar with common machine learning algorithms such as GBDT, collaborative filtering, LSTM (with practical experience); or familiar with text mining work (e.g. keyword extraction, sentiment analysis, content summary and visual presentation)
4. Good at learning, with good communication and independent problem solving skills
5. Familiar with graph theory, graph storage, and practical experience is preferred
6. Experience in distributed data processing is preferred (e.g. Hadoop, Spark)
7. If you have experience in data competitions such as Kaggle, or experience in publishing papers in related fields, please provide relevant information as an attachment when you provide your resume
2. Have a solid data processing and data analysis experience for more than 2 years
3. Familiar with common machine learning algorithms such as GBDT, collaborative filtering, LSTM (with practical experience); or familiar with text mining work (e.g. keyword extraction, sentiment analysis, content summary and visual presentation)
4. Good at learning, with good communication and independent problem solving skills
5. Familiar with graph theory, graph storage, and practical experience is preferred
6. Experience in distributed data processing is preferred (e.g. Hadoop, Spark)
7. If you have experience in data competitions such as Kaggle, or experience in publishing papers in related fields, please provide relevant information as an attachment when you provide your resume
其他条件
学历：大学
科系：资讯管理相关
年資：4年以上工作经验
管理责任：不需负担管理责任
出差外派：无需出差外派
科系：资讯管理相关
年資：4年以上工作经验
语文：
英文：聽/精通 說/精通 讀/精通 寫/精通
出差外派：无需出差外派
公司福利
法定项目：勞保,健保,陪產假,產假,特別休假,育嬰留停,女性生理假,勞退提撥金,產檢假,就業保險,職災保險
