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
