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Data Science Lead Emerging Markets

応募後で応募 求人ID R0017265 掲載日 03/24/2020 Location:Zurich, Switzerland

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Job Description

Are you looking for a patient-focused, innovation-driven company that will inspire you and empower you to shine? Join us as a Global Data Science Lead in our Office in Zurich, Switzerland.

Here, you will be a vital contributor to our inspiring, bold mission.

As our Global Data Science Lead, you will be working in the GMS Emerging Market region. Your typical day will include:

  • Driving design, execution and implementation of the overall GMS Data Science strategy for the GMS Emerging Market
  • Develop and own detailed GMS Emerging Market scale-up and delivery execution road-map for data science and manages respective functional and cross-functional interdependencies.
  • Review data science possibilities/initiatives/requests in collaboration with IT and GMSGQ business stakeholders.
  • Manage, gather and execute GMS Emerging Market data science needs and execution of initiatives in collaboration with respective stakeholders and advise on the respective short and medium focus
  • Review and establishes internal and external data science capabilities within GMS Emerging Market
  • Provide the Data Science link across local, functional and global GMS Data Science, IT, Engineering and GMS Emerging Market.
  • Execute and drive the data science training for GMS Emerging Market in collaboration with GMSCI Data Science Training excellence.
  • Ensure GMS Emerging Market representation in GMSGQ data science community.
  • A firm grasp of industry, scientific and digital, artificial intelligence, machine learning and data science trends and market conditions, to develop solutions enhance compliance and quality of life for patients
  • Provide patient-centred best in class GMS Data science for the GMS Emerging Market, establishes data science talent and elevate organisational performance

EDUCATION, BEHAVIOURAL COMPETENCIES AND SKILLS:

  • 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.
  • Experience in applying and executing Digital/Big Data Analytics/ Artificial Intelligence/Machine Learning, Machine Learning algorithms, Respective programming knowledge
  • Fluent in English

Digital & Data Science Skills:

  • Experience 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 advantageous
  • Prior experience of Biostatistics, stochastic modelling and decision trees is a strong asset
  • Strong knowledge of Statistical Process Control Expertise in Bayesian statistics:
  • Experience in Density estimation
  • Solid knowledge in Bayesian Hypothesis Testing. Knowledge in ANOVA and forecasting techniques (ARIMA, RMA, NARX)
  • Expertise in Signal Processing, Control Systems, Mechatronics
  • Learning algorithms, respective programming knowledge
  • Capabilities to translate business needs into data analytics concepts and the other way
  • Hands-on, able to implement and execute data science initiatives, analysis, machine learning
  • High level project management skills

WHAT TAKEDA CAN OFFER YOU

At Takeda, we are transforming the pharmaceutical industry through our R&D driven market leadership and being a values-led company. To do this, we empower our people to realise their potential through life-changing work. Certified as a Global Top Employer, we offer stimulating careers, encourage innovation, and strive for excellence in everything we do. We foster an inclusive, collaborative workplace, in which our global teams are united by an unwavering commitment to deliver Better Health and a Brighter Future to people around the world.

Empowering Our People to Shine

Discover more at takedajobs.com

Locations

Zurich, Switzerland

Worker Type

Employee

Worker Sub-Type

Regular

Time Type

Full time

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