Position Description :
The CGT Capacity Analytics and Modeling Manager position is designed to support an emerging business’ needs for global capacity simulation, productivity improvement and investment decisions to ensure reliable supply at lowest total cost.
Mine, analyze, and model large structured and unstructured datasets, and apply advanced statistical predictive models and leading machine learning algorithms to explore strategic business opportunities and to formulate actionable recommendations.
Provide capacity related advanced analysis with prudent methodology including manufacturing volatility, demand & market, tank life, and inventory.
Creatively translate business problems into data science initiatives with appropriate methodology (e.g., neural networks, Bayesian, regression, clustering, dimensionality reduction, etc.
and evaluate the results rigorously.
Contribute to team development, effectiveness and success by sharing knowledge and good practice, working collaboratively with others to create a productive, diverse and supportive working environment.
Setup direction and interpret data for management team.
Strong network, proven leadership and respect among peers
Analyze new business growth within CGT by leveraging existing networks and expertise
Support OPS team with the methodology for ad hoc analysis
Education & Experience : Education
Bachelor degree and above. Major in engineering, industrial engineering, supply chain, mathematics, statistical or other related discipline
MBA degree and engineering background is preferred
Extensive experiences in complicated data analysis / data modeling is required
8+ years in engineering, supply chain, global capacity planning, manufacturing operation is preferred.
Required Skills :
Comfortable with mining massive volume of data for quick insight discovery
Effective communication, interpersonal, organizational, problem solving, and presentation skills
Detail-oriented and zero tolerance on quality / accuracy issue
Desired Skills :
Experience working across cultures with a virtual team
Experience to work with sales planning, engineering and manufacturing
Proficient in SAS (covering base SAS, SAS STAT, Enterprise Miner) and Microsoft R / Python (SciKit-Learn, Keras, TensorFlow, Theano and etc.) is preferred
Travel Requirements : National : 25% to 50%