Roles/Responsibilities：

· Responsible for the architecture design of models / strategies / algorithms for the innovative applications, including but not limited to predictive analysis, natural language processing etc.

· Identifies unique opportunities to collect new data. 

· Designs new processes and builds large, complex data sets.

· Strategizes new uses for data and its interaction with data design.

· Locates new data sources, analyzes statistics and implements quality procedures.

· Performs data studies of new and diverse data sources.

· Finds new uses for existing data sources.

· Conducts statistical modeling and experiment design.

· Discovers “stories” told by the data and presents them to other scientists and business managers.

· Tests and validates predictive models.

· Builds web prototypes and performs data visualization.

· Conducts scalable data research on and off the cloud.

· Implements automated processes for efficiently producing scale models.

· Designs, modifies and builds new data processes.

· Generates algorithms and creates computer models.

· Proficient programming in Python, R, and SQL (Structured Query Language).

· Hadoop, NoSQL, Java are strong plus.

· Programming on scalable/Big Data language such as Scala/Spark is a plus.

Background/Experience/Credentials:

• Bachelor's degree or above, will graduate in 2021;

• Major in Computer Science, Information Technology, Math, Statistics and  related disciplines

• Good command of written and spoken English;

• Possesses a working knowledge of statistics, programming and predictive modelling;

• Background or strong interest in related technology solutions;

• Demonstrates excellent code writing abilities;

• Has strong critical thinking skills and the ability to relate them to the products or services the company is producing;

• Proficient programming on scalable/Big Data language  such as Scala/Spark is a plus;

• Shows strong knowledge of basic and advanced prediction models.

• Possess a combination of creative abilities and business knowledge;

• Demonstrate good verbal and written communication skills as well as the ability to bridge the gap between data science and business management;

• Start from internship and can be converted into full time employee after graduation based on internship assessment