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Position: Data Science Lead
Institution: Syngenta
Location: Durham, North Carolina, United States
Duties: Develops, coordinates, and provides data science leadership and support for related projects in Breeding Innovation Pipelines at the Seeds Development Function level; Requires in-depth knowledge and experience in Data Mining, Machine Learning and Compute Vision including mastery of techniques/methods/scientific theories and subject matter expertise; Typically works on complex problems in which analysis of situations or data requires an in-depth evaluation of various factors and potentially the design of new analytics approaches; Responsible for development of new and improvement of existing processes, products and systems in defining, designing and enhancing our ability to support data-driven decisions in a broad range of contexts; Identify data needs and provide recommendations for the development of the global data strategy
Requirements: Ph.D. in Data Science or Applied Mathematics; Technical understanding of plant breeding and environmental trialing; 10+ years of experience in data science methods applied to the design and analysis of experiments; including programming, multivariate statistics, probability, and spatial statistics; Significant experience in designing new analytics approaches customized with regards to specific constraints
   
Text: Data Science Lead Develops, coordinates, and provides data science leadership and support for related projects in Breeding Innovation Pipelines at the Seeds Development Function level; Requires in-depth knowledge and experience in Data Mining, Machine Learning and Compute Vision including mastery of techniques/methods/scientific theories and subject matter expertise; Typically works on complex problems in which analysis of situations or data requires an in-depth evaluation of various factors and potentially the design of new analytics approaches; Responsible for development of new and improvement of existing processes, products and systems in defining, designing and enhancing our ability to support data-driven decisions in a broad range of contexts; Identify data needs and provide recommendations for the development of the global data strategy Ph.D. in Data Science or Applied Mathematics; Technical understanding of plant breeding and environmental trialing; 10+ years of experience in data science methods applied to the design and analysis of experiments; including programming, multivariate statistics, probability, and spatial statistics; Significant experience in designing new analytics approaches customized with regards to specific constraints
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