YOUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role, Data Scientist Intern, are to: 

• Develop strategies to identify new opportunities and expand existing methods, provide insights, and build practical solutions to complex business problems;
• Apply advanced analytics skills to turn data into competitive advantage and make recommendations for data-driven business decisions.

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:

• Pursuing a master’s degree in Mathematics, Computer Science, Engineering, Economics, or other quantitative disciplines or a Ph.D. in similar disciplines;
• Experience applying sophisticated scientific methods in the field of analytics using statistical and mathematical programming packages such as R, Python, Scala;
• Understanding of advanced analytics methods;
• Ability to turn complex data into predictive and prescriptive insights;
• Experience analyzing and presenting complex data and proven problem-solving abilities;
• Exceptional organizational, interpersonal, and written communication skills;
• Ability to work in a matrix environment, influencing people at varying levels of responsibility.

Preferred Qualifications:

• Experience modeling industry and market trends, competitive threats;
• Ability to understand the market through product analytics, sales insight, market research and competitive analysis;
• Customer analytics, customer profiling and segmentation;
• Evaluate customer segment characteristics across multiple dimensions, producing customer demographic, psychographic, financial, and behavioral profiles to drive client marketing strategies and tactics;
• Experience with Hadoop, Spark, cloud computing, SFDC and SAP platforms and data, Spatial-temporal modeling;
• Experience working with agricultural/biological scientific data;
• Strong publication record inleading scientific journals;
• Drive for translating business problems into research initiatives that deliver business value;
• Structure complex and ambiguous problems, synthesize findings, develop innovative options, and make recommendations.