Job Description:

  • Work closely with our data scientist team to uncover insights, deploy state-of-the-art algorithms, and build practical solutions on massive user and product data.
  • Build core machine learning models as well as end-to-end product to support business applications such as anti-fraud, credit scoring, face recognition, production information mining, and e-commerce knowledge graph, etc.
  • Analyze massive data and conduct feature engineering by large-scale data mining
  • Strong knowledge in one of the following machine learning areas will be an advantage: 
    • Deep learning
    • NLP
    • Face recognition and video analytics
    • Knowledge graphs
    • Risk modeling
    • Web crawling
  • Research the state-of-the-art techniques in deep learning, reinforcement learning areas to solve challenging problems.
  • Setup real-time data pipeline and build reliable dataset for various tasks.
  • Experience in semi-supervised, unsupervised models, and multi-modal deep learning will be an advantage but not pre-requisite.
  • Experience working on credit risk related products will be an advantage but not a prerequisite

Requirements:

  • 2 years working experience with a programming language such as Python
  • Experience on SQL, Spark, Kafka
  • Knowledge on areas such as NLP, Computer vision, Deep learning
  • Experience on elasticsearch, JanusGraph, Apache Gremlin
  • Experience in OpenCV/Tensorflow/Caffe machine learning framework

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