About the Team Our mission is to optimize the variety & cost-saving of assortments and the speed & quality of fulfillment to ensure the user experience of global e-commerce services.
- Build global logistic and warehousing network, improve operations efficiency and reduce operational cost with data analysis, machine learning and operation research methods.
- Create supply chain's data portrait and knowledge graph in various dimensions such as vendors, commodity, place of origin, inventory, production capacity and quality of fulfillment, etc. Predict user needs in different countries and regions, guide inventory preparation and fulfillment, and implement effective pricing. From a comprehensive B-C perspective, optimize platform efficiency and enhance user experience through diverse supply chain collaboration means.
- Optimize merchant/merchandise supply. Mine high-quality global merchant leads, establish outreach and conversion mechanism to drive merchant growth, and provide continuous incubation and support after merchant onboard. Track international e-commerce trends and TT content trends, identify best-selling product leads and improve the supply of high-quality and affordable goods. Collaborate with the supply chain system to build systematic product growth and operation capabilities.
We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.
Responsibilities
- Responsible for the development of deep learning and operations research models and related intelligent systems for the supply chain and logistics of the global E-Commerce business.
- Utilize e-commerce big data and deep learning models to predict end-to-end estimated time of arrival (ETA), and some logistics events such as failed delivery, delivered but not received to enhance the user logistics experience. Build logistics network knowledge graphs and predict the spatio-temporal trajectory sequence of express packages through deep learning, statistical inference and other algorithmic methods. Use NLP and LLM algorithms to handle address problems such as address verification and address suggestion.
- Utilize time series forecasting techniques to predict sales at different granularities and horizons, such as warehouse-level manpower forecasting, inventory-level demand forecasting etc. We need strong machine learning and deep learning skills to detect important factors and model the relationship between the future and history.
- Participate in the development of merchant and merchanise related algorithm systems including potential merchants mining, tiering and outreach, seller growth diagnosis and seller mission recommendation system, etc. Work closely with e-commerce supply related operation teams and product teams to achieve the growth goal of e-commerce business.
- Based on the massive e-commerce related information mined from different resources, predict the traffic/conversion performance of merchandises using different kinds of machine learning methods, improve the efficiency of merchandise operation strategy and pricing/subsidy strategy, and assist in optimizing traffic distribution. And finally achieve the goal of merchandise growth under certain cost/profit target at the same time.
Minimum Qualifications
- Individuals who are completing or have recently completed a PhD degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
- Proficient in machine learning and statistics, familiar with the principles and model structures of common machine learning and deep learning algorithms for classification, regression, and clustering, with practical application experience.
- Proficient in programming languages such as Python/Java, possessing excellent coding abilities, and familiar with at least one common machine learning/deep learning framework (TensorFlow/PyTorch etc.).
Preferred Qualifications
- Frontier AI Technologies: hands on experience applying LLM and AI Agents in business scenarios is preferred
- Demonstrates a spirit of exploration, outstanding data analysis capabilities, strong initiative, and excellent teamwork and communication skills.
- Bonus points for having published papers at conferences such as KDD, NeurIPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RecSys, or having participated in data mining/machine learning competitions.