Essential Responsibilities:
In this role, the Operation excellence data scientist is responsible for large scale data analysis on commercial data and W2W process quality. Conduct sophisticated quantitative analysis and drive deep data-driven business insights for critical decision making. Explore diverse data sources and learn from different types of data to get insights and estimate future trends. Drive predictive commercial analytics digitization related to commercial applications and proved data source, He/she will have the opportunity to contribute directly to the features and capabilities deployed in digital tools.
Key responsibilities:
Ÿ Develop customized commercial operation metrics models and algorithms to generate high-impact data insights
Ÿ Process and publish commercial operation metrics with proper frequency aligned with business rhythm, identify emergent trends and opportunities for growth
Ÿ Large scale commercial data dig out with multiple data source mapped or related applications to support commercial and product strategy
Ÿ Set up processes and framework for responding to data/system issues with cross functional teams in a timely manner
Ÿ Scouting, identification and tracking of new trends and emerging technologies in China, derive impacts on GEHC commercial digital thread
Ÿ Uses advanced techniques that integrate traditional and non-traditional data sets to enable analytical solutions
Ÿ Partner with IT to develop scalable, efficient, automated processes for customized metrics or prototypes that can be used to drive business decisions
Ÿ Builds analytical solutions leveraging internal and external applications to deliver value and create competitive advantage, develop predictive analytics applications
Ÿ Applies predictive analytics, machine learning, simulation, and optimization techniques to generate management insights and enable customer-facing applications

Qualifications/Requirements:
Qualifications/Knowledge and Skills Required

Ÿ Master or equivalent degree in Mathematics, Statistics, Computer science.
Ÿ Strong/expert knowledge/back ground in Data Science, Bid Data, Data Analytics, Data mining
Ÿ Passion for innovation & entrepreneurial mindset
Ÿ Strong team player with autonomous and efficient working style
Ÿ Excellent communication skills, fluent in English (oral and written)
Ÿ Experience in manipulating large and complex datasets through statistical software, such as Python, SAS, R or SPSS
Ÿ Highly skilled in drawing relevant conclusion from analyses; relating analyses to business outcomes and strategic goals
Ÿ Hands-on experience in solving complicated problems in different scenario using advanced analytics techniques
Ÿ Excellent interpersonal skills and effectiveness in working across geographical boundaries
Ÿ Ability to translate business requirements into mathematical models and data science objectives to achieve measurable business outcomes
Ÿ Deep understanding of algorithms and AI
Ÿ Demonstrated organizational and time management skills
Ÿ Strong sense of urgency with a demonstrated record of meeting commitments
Ÿ Demonstrate strong execution skills and ability to drive result and changes

Preferred Qualifications:
Ÿ Capable of handling big data. Prior experience with Teradata, Hadoop is big plus.
Ÿ 3+ years in predictive modeling, large data analysis and computer science
Ÿ 3+ Experience in a specific industry (e.g. commercial and sales operations) are preferable
Ÿ High level proficiency with statistics tools: SPSS, SAS, R
Ÿ Master big data foundation support framework is preferred: Hadoop/Spark (Map/Reduce, HBase/Hive/HDFS, Streaming, Kafka, Flume, Yarn), ElesticsSearch /Solr, Redis and so on.

About Us:
GE (NYSE:GE) drives the world forward by tackling its biggest challenges. By combining world-class engineering with software and analytics, GE helps the world work more efficiently, reliably, and safely. GE people are global, diverse and dedicated, operating with the highest integrity and passion to fulfill GE’s mission and deliver for our customers. www.ge.com

Locations: China; ShangHai; Shanghai