Data Scientist

Data Scientist Apply Now! Responsibilities Collaborate with the business intelligence team to utilize historical data in forecasting future trends and detecting fraud. Collaborate with the operations team and the data engineering team to design various systems, which include, but are not limited to: User activity monitoring and anomaly detection Content moderation system Systems for optimization operation workflows Work with the data engineering team to design and implement recommendation systems at scale. Requirements Fluency in common data science Python libraries, including but not limited to numpy, pandas, scikit-learn. Fluency in several machine learning frameworks, including but not limited to tensorflow / pytorch, keras, theanos, pyspark Proficiency in the basic software development lifecycle and low-level code optimization. A self-directed learning mentality. Comfortable working in an English-speaking environment. Good to have Knowledge in deep learning based recommender system such as DLRM, Wide & Deep , and NCF. Expertise in building LLM applications and familiarity with foundational models (LLaMA, BERT, GPT, Mixtral 8x7B) and frameworks, such as langchain, weights & biases as well as retrieval mechanisms with vector databases such as pinecone and weaviate. Experience in leading a team and providing mentorship. 部門 Engineering - Data 職位 Data Scientist 地點 臺北 遠端狀態 混合 關於SWAG SWAG 創立於 2016 年 8 月，最初的產品構想，是要打造一個能串連網紅創作者及用戶的 PGC 流量變現的平台，讓粉絲可以無時無刻的與心儀的網紅互動、讓網紅可以透過人氣實現獲利。 透過豐富多元的內容及強大的行銷推廣，目前平台有超過 400 萬註冊用戶及數千位內容提供者，用戶遍及臺灣、香港、澳門、新加坡、馬來西亞及歐美等，並獲得數十位 YouTuber 網紅大力推薦；成為亞洲最大的影音串流平台。 號 官方在 2018 上半年開啟了 swag.live ，使用者可以透過網頁直接開啟 SWAG，並陸續加入了直播、一對一私訊聊天以及影片解鎖等新功能。 如今 SWAG 定位為亞洲最大的影音串流社交平台，並且持續的拓展國際市場。