Data Science Manager 数据分析产品经理

Randstad

职位概述Our client is global company with total capital over 20 billion USD and 60,000+ employees worldwideKey Responsibilities

Understand data & analytics challenge faced by business to identify digital-enabled opportunities
Work with key business stakeholders, BG digital head and other relevant digital/IT staff to co-define data & analytics strategy (e.g. prioritized value cases, data governance framework, analytics approaches and technical platforms)
Assist data & analytics business owner to propose process & organization optimization to achieve smooth execution of above framework & approaches
Translate data & analytics related business requirements into actionable technical realization approaches and features of data & analytics technical platform/product  Work with digital project manager, solution architect, DevOps engineer and 3rd party vendors to develop and deploy country-level data & analytics technical platforms
Guide value case discovery at BG level and oversee development & deployment of BG-level data & analytics technical products (e.g. dashboard, analytics technical approaches)
Lead data & analytics projects at China level if bandwidth allows(e.g. China data warehouse)

Qualifications

Bachelor's or Master of Science, physics, computer science, business informatics, mathematics, engineering or similar fields.
10+ years of working experience in data science or advanced data analysis. Management experience  Familiar with agile methods and advanced experience in pattern recognition and predictive modeling
Expertise with scripting tools, e.g. Python, Pearl or JavaScript, statistics tools, e. g. Matlab, SAS, relational databases, e. g. Oracle, SAP R/3 or MS SQL, Query tools (SQL or noSQL) and Business Intelligence tools, e. g. Power BI.
Knowledge of Machine Learning techniques, including decision tree learning, clustering, artificial neural networks, etc.
Knowledge and application experience in advanced statistical techniques and concepts, including, regression, distribution properties, statistical testing, etc.  Experience/knowledge in statistics and data mining techniques, including, random forest, GLM/regression, social network analysis, text mining, etc.
Have sharp analytical and problem-solving skills as well as excellent team spirit.  Experience using and developing data architectures

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