YOUR TASKS AND RESPONSIBILITIES

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

• Drive research lab optimization by creating machine learning models that suggest optimal lab remediation decisions;
• Enable automated alerting of lab process failure by determining optimal statistical tests and analyses to empower the research lab with same-day failure detection and prediction;
• Create and ensure adoption of machine learning models that drive Crop Science pipeline decisions;
• Integrate solutions into production processes by partnering with end users to determine optimal consumption method of model output (e.g.
  automated emails versus webapps);
• Form partnerships with cross-functional teams in Bayer (Breeding, Product Supply, IT) to drive unified reporting and optimization of
  complex workflows that span functions and countries;
• Independently perform statistical analysis, computer programming, predictive modeling, and experimental design;
• Present compelling, validated stories to all levels of organization,
  including peers, senior management, and internal customers to drive both strategic and operational changes in business;
• Provide technical contributions leveraging business acumen in a fast-paced team environment to accelerate our efforts on building an
  analytics-driven product pipeline.
   

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 pursuing a BS degree or higher in any of the following fields: Machine Learning, Electrical/Industrial Engineering, Operation Research, Statistical Genetics, Statistics, Biostatistics, Bioinformatics, Genomics, Computational Biology, Applied Mathematics, Computer Science or other related quantitative disciplines.  
• Intermediate proficiency in computational skills and level of experience building data models using R, Python, or other statistical programming languages;
• Intermediate proficiency in machine learning modeling, algorithms, and concepts;
• Strong communication competencies to include presentations and delivery of analyses in a clear, concise and actionable manner to extended team and small groups of key stakeholders.

Preferred Qualifications:

• Shiny or other webapp framework experience.