Responsibilities
About The Team The e-commerce industry has seen tremendous growth in recent years and has become a hotly contested space amongst leading Internet companies, and its future growth cannot be underestimated.
With millions of loyal users globally, we believe TikTok is an ideal platform to deliver a brand new and better e-commerce experience to our users. Our product engineering team is responsible for building an e-commerce ecosystem that is innovative, secure and intuitive for our users. We are looking for passionate and talented people to join us as we drive the future of e-commerce here at TikTok.
Responsibilities
- Responsible for development of data-empowered capabilities for e-commerce platform, enable different e-commerce verticals to extract and apply key insights from oceans of data to meet their business needs.
- Data mining for e-commerce, 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.
