Our client is one of the leading global e-commerce players with millions of subscribers/ users globally.
With strategic expansion plans and to serve clients effectively in various geographical locations, they are further strengthening their teams in Singapore.
- Optimize the personalized recommendation algorithms for large-scale e-commerce platforms, including product recommendations for various platforms operated including live streaming, short video recommendations, etc.
- Utilize techniques such as representation learning, graph modelling, deep learning, transfer learning, and multi-task learning to enhance the efficiency of information matching, allowing users to easily find high-quality products.
- Mine and analyze massive user behaviour data to model long-term and short-term user interests, as well as predict potential interests, in order to improve the accuracy of recommendations.
- Automatically discover high-quality, professional, and well-reputed products and influencers through algorithmic methods, fostering a positive feedback loop and optimizing the content e-commerce ecosystem.
- Innovate models and algorithms based on the characteristics of content e-commerce, aiming to build industry-leading recommendation algorithms and systems.
- Strong foundation in algorithms and data structures with excellent coding skills.
- Solid understanding of machine learning, familiar with commonly used algorithmic models such as CF, MF, FM, word2vec, LR, GBDT, DNN, Wide&Deep.
- Familiarity with any of the following open-source tools: xgboost, TensorFlow, PyTorch.
- Proficiency in C++ and Python programming languages, familiar with Linux development environment.
- Excellent learning ability and good teamwork spirit.
- Research or project experience in personalized recommendation, advertising, information retrieval, natural language processing, machine learning, or related fields. Would be an added advantage
- Publication of papers at conferences such as KDD, NeurIPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RecSys, or participation in data mining/machine learning competitions would be a plus