Job Description & How to Apply Below
Drives the design, execution and implementation of the overall Global GMSGQ(Global Manufacturing & Supply, Global Quality) Big Data and analytics strategy. Provides the link across local, functional and global GMSGQ data analytics, IT and GMSGQ business.
Drives the design, execution and implementation of advanced analytics for GMSGQ (e.g. Continuous Process Improvement, end-to-end Simulation, advanced statistics, modeling simulation)
Develops and owns detailed scale-up and delivery execution roadmap for data analytics within GMSGQ and manages respective functional and cross-functional interdependencies
Owns, manages and executes process monitoring and process improvement in collaboration with local and functional GMSGQ data analytics (e.g. descriptive statistics and visualization, statistical process control, out-of-the-box-tools)
Owns, manages and executes respective Reporting in collaboration with local GMSGQ and functional data analytics (e.g. automated daily/monthly/annual, Stability Analysis Targets)
Gathers, identifies and reviews GMSGQ data analytics possibilities/initiatives/requests in collaboration with IT and GMSGQ business stakeholders. Advises on the respective short and medium focus.
Drives and executes on digital GMSGQ Strategy, Technology and Innovation (e.g. Productivity Analysis, Key Performance Indicator tracking, Interdependencies, Evolution of Internet of Things)
Builds up and owns global/functional/local GMSGQ data analytics community.
Expertise and experience in Digital/Big Data Analytics/ Artificial intelligence/Machine Learning:Expertise in Signal Processing, Control Systems, MechatronicsStrong knowledge of Statistical Process ControlExperience in Machine Learning algorithms (CNN, SVM, LSTM, etc.), Respective programming knowledge of either MATLAB/Python/R required, further skills such as C++, SQL etc. are advantageousExperience in quality mapping of parameters is a plus
Expertise in Bayesian statistics:Experience in Density estimationSolid knowledge in Bayesian Hypothesis Testing,Solid knowledge in ANOVA and forecasting techniques (ARIMA, ARMA, NARX)Prior experience of Biostatistics, stochastic modelling and decision trees is a strong asset
University degree of science/business. Advanced degree is required (Master/MBA and/or PhD), e.g. in Engineering , Mathematics, IT or Physics with focus on either Control Theory/Statistics/Mechatronics, Information/Operation, Management/Strategy, Technology and Innovation Management
Capabilities to translate business needs into data analytics concepts and the other way
Hands-on, able to implement and execute initiatives
High level project management skills
Ability to interface with international stakeholders and to connect internal and external data analytics experts of both academia and industries
Fluent written and spoken English
Willingness to travel to various internal/external Takeda meetings and events
International travel will be required
Job ID R0014623
Less than 1 Year
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