The Statistician/Data Scientist will be responsible for all advanced statistical methods utilized for improving product quality, production yield, and factory effectiveness as well as finding the root-causes, along with other consulting services such as customer targeting and lead scoring in support of sales and marketing activities worldwide.
• Design, implement, and refine advanced statistical/Machine Learning models to support product quality improvement, increasing yield and factory effectiveness.
• Cultivate strong relationships with production line engineers, IT, and other key stakeholders to ensure alignment of modeling initiatives with company objectives and to identify new hypotheses for model improvements.
• Scale out modeling capacity by driving infrastructure improvements such as automation of data preparations, model training, implementation, and optimization.
• Support integration of models into tools for use by product engineers and business analysts.
• Engage with customers to develop and customized data analytics solutions to address special needs.
• Address ad hoc queries from management and present actionable recommendations in a clear, concise, and convincing manner.
• Communicate the application and benefits of using various predictive modeling techniques to improve decision-making to customers and stakeholders.
• Collaborate effectively with team members, whether leading projects or supporting initiatives led by others.
• Provide direction, training, and guidance to less experienced team members.
- 1至3 人
- -- 聽 /中等、說 /中等、讀 /中等、寫 /中等
- • Master or PhD degree in a field where there is intensive training
in quantitative methods such as Statistics, Machine Learning,
Electrical and Computer Engineering, Economics, Physics,
Industrial Engineering, or Operation Research. PhD prefer.
• Research field in Design of Experiment, Response Surface
Methodology, Survey Sampling, Time Series, Temporal Data,
Bayesian Statistics, Survival Analysis, High Dimensional Data
Analysis, Nonlinear Models, Linear/ Nonlinear Programming,
Optimization, or Classification would be a big plus. A strong
candidate must hit at least 1-2 fields above.
• 5+ year experience (for senior) in successfully developing and
implementing predictive models in the production environment.
• Professional in SAS, R, Python, MatLab, or SQL, with practical
expertise in programming and statistical modeling procedures
including Linear Regression, Logistics Regression, Generalized
Linear Model, Mixed model, Survival Analysis, and ARIMA model.
• Demonstrated skills in data cleansing and transformations in the
creation of predictor variables from complex data structures.
• Knowledge of scorecard development, performance
measurement, and business intelligence software solutions.
• Detail-oriented and interested in applying quantitative methods
to solving engineering and business problems.
• Ability to thrive in a dynamic, collaborative team environment.