Responsibilities
1. Data warehouse and development: Starting from the end-cloud link, design and implement efficient end-cloud data extraction and feature cleaning links, link the end-cloud to build efficient automated analysis and content understanding capabilities, participate in data warehouse and modeling of Douyin live broadcast experience direction, and improve the usability and quality of data 2. Model deployment and services: Promote the implementation of algorithms in business scenarios, be responsible for the integrated deployment of device and cloud of machine learning & deep learning models, and integrate existing information and capabilities into scalable model services 3. Data mining and analysis: Responsible for the mining and analysis of Douyin live client experience data, build device-cloud integrated data understanding capabilities through data insights, qualitative and quantitative analysis and model construction, and optimize user viewing and broadcasting experience 4. Business collaboration and strategic support: In-depth understanding of the live broadcast business, from an experience perspective, linking the client experience and DA teams to provide device-cloud collaboration solutions based on data and algorithms 5. Technical research and methodology precipitation: Summarize and optimize data analysis & research methodologies applicable to the live broadcast experience business, and focus on industry cutting-edge technologies.
Qualifications
1. Bachelor degree or above, mathematics, statistics, computer-related majors are preferred 2. Proficient in programming languages such as Python, Scala, Java or Go, with solid coding skills and good awareness of programming standards 3. Proficient in SQL, master machine learning and deep learning related algorithms, familiar with frameworks such as Scikit-learn, TensorFlow, PyTorch (any one) familiar with big data processing frameworks such as Hive, Spark, Flink, Kafka, etc. 4. Familiar with machine/deep learning engineering architecture, including deployment, operation and maintenance, and online training architecture (client or server) 5. Data awareness: sensitive to business and data, with excellent problem analysis and problem-solving abilities, and the ability to quickly understand and abstract business requirements.
