YOUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role, Yield & Disease Traits Intern, are to:

• Build on an existing statistical model that considers germplasm, trait, and environmental data; and isolating environmental effects on performance of key phenotype of yield and disease traits.  
• Research and develop innovative methodologies and models to understand and exploit interactions among germplasm, trait, and environments, with the ability to predict trait performance in different germplasm under varying environmental conditions.
• Explore, manage, and model large and diverse field derived datasets;
• Analyze and ascertain the quality of data, working work with the data quality team to resolve issues;
• Design and prototype models using statistical modeling, process modeling, and other techniques, such as machine learning;
• Implement and test algorithms and techniques relevant to achieving project objectives;
• Demonstrate the applicability of the models and deploy them to Stakeholders;
• Select the most appropriate modeling techniques and data visualization for large datasets;
• Assist with high-level analysis, design and code reviews;
• Partner with IT and data science team members to deploy models in the cloud
• Work closely with a team of world-class data scientists, agronomists, breeders, and plant scientists to deliver impactful scientific research.
   
   

WHO YOU ARE

Your success will be driven by your demonstration of our LIFE values.  More specifically related to this position, Bayer seeks an incumbent who possesses the following:

Required Qualifications:

• Currently enrolled at an accredited university located in the U.S. pursuing a M.S. or Ph.D. in Computer Science, Statistics, Data Science Mathematics, Computational Biology, Plant Breeding or related discipline;
• Demonstrated experience working with large, complex, and incomplete data sets;
• Strong analytical and quantitative problem-solving ability, with demonstrated ability to build, test, and iterate on a variety of model forms;
• Skilled in the use of R, Python, and SQL

Preferred Qualifications:

• Strong attention to detail;
• Strong problem solving and critical thinking skills;
• Ability to communicate complex ideas in a clear, precise and actionable manner;
• Demonstrated interpersonal and communication skills, including an ability to interact with and establish good working relationships with diverse individuals;
• Results oriented with ability to work independently.