<About the job>：
The Data Science & AI team of headquarter IT is developing the frontier and practical analytic technologies that enhance the data value. As the data scientist, you'll join the AI/Big Data Analytics program/projects related to management topics, including Commercial/Industrial Engineering/Supply Chain/Financial Performance/Operation...etc., to build the model or algorithm to empower data-driven & analytics-driven for driving business value from data insights in this world-class company (Fortune Global 500, 22nd).
<Job Description>：
．Design, implement and refine advanced Statistical Modeling/Machine Learning/Deep Learning/Numerical Simulation/Optimization Algorithm Models(at least one of the fields)
．Ensure alignment of modeling initiatives with the requirement goal defined by key stakeholders and company objectives and identify new hypotheses for model improvements.
．Executing big data analysis and predictive analytics projects include feature engineering, model building, algorithm development, etc.
．Works closely with a team of data system analysts, business data analysts, data engineers, data platform architects, etc.
．Collaborate effectively with team members, whether leading tasks or supporting initiatives led by others.
．Self-motivated, Result-oriented, and interested in applying quantitative methods to solving business and engineering problems.
<Skills>
．Experience with any one of Machine Learning, Statistical Modeling, Deep Learning(Nature Language/Image), Econometric Modeling, Optimization Algorithm(OR), Numerical Simulation..., etc., model/algorithm building of the practical application in the industry.
．Familiarity with programming languages like Python or R, or Java. (Good programming skills in Python is a plus).
．Advanced ability to perform Exploratory Data Analysis and working knowledge of statistics.
．Ability to visualize data in the most effective way possible for a given task, especially visualize models and results and debug and troubleshoot code and models.
．Big on finding the many insights based on the data and being passionate and patient about working with complex data.
