Machine Learning Engineer (Data Mining) - Global E-Commerce

e, building tagging system based on massive data, analysing user, traffic, e-commerce and other data, combining with business to improve GMV.

• Data analysis, mining, model specific productization; understanding of e-commerce business, able to work with PM to continuously optimize data products based on data-driven.
• Develop data mining pipelines to extract data assets (eg. entity labels) from aggregated data and enable the extraction of actionable insights from large volumes of domain data.
• Design and development of various strategies, algorithms and machine learning techniques to improve the accuracy and coverage of extracted data assets.
• Analyze e-commerce data-related business problems and abstract them into data-related requirements that are then implemented to help resolve key business problems.

Qualifications

Minimum Qualifications

• B. Sc or higher degree in Computer Science or related fields from accredited and reputable institutions.
• 5 years experience in data structures and algorithms, familiar with one or more: machine learning, natural language processing, data mining.
• Familiar with one of the Python/Java/Go/C++ programming languages.
• Familiar with common data processing technologies (Hadoop, Spark, Hive, Storm, Flink), with demonstrable coding skills.
• Familiar with common data mining techniques and machine learning algorithms (GBDT, Xgboost, FM, DFM, etc.), and familiar with their principles and scope of application.
• Proficiency in data mining, machine learning tools and common frameworks (TensorFlow, Pytorch).

Preferred Qualifications

• Continuous learning, keeping up with the latest research directions and results in the field of machine learning, for the exploration of big data applications in various vertical areas.
• In-depth research experience in analysis and mining of user behaviour data and construction of user portraits.
• Data mining experience in vertical industries (e-commerce, finance, games, travel, real estate, etc.).
• Development and optimisation of advertising and recommendation algorithms.