Bayer Crop Science is passionate about using Data Science and Information Technology to improve agriculture. Data Science is critical to the success of Bayer Crop Science today and in the future as we transform into an Information Services company. We are seeking a Data Scientist to join our IT Decision Science team as an intern/co-op in the area of genome analytics. The IT Decision Science team looks to find creative and innovative solutions to enable success within our R&D, supply chain and commercial organizations while identifying and capitalizing on new opportunities to maintain and grow our position as a digital agriculture market leader. The ability to examine and optimize our current methods coupled with an eye on the future lends itself to a unique opportunity within Bayer Crop Science and our team. This is an exciting opportunity for a talented and passionate individual to join a multidisciplinary team of data scientists and engineers who work on real world problems.
The primary responsibilities of this role, Data Scientist Co-Op, are to: 

  • Develop mathematical models (e.g. statistical, machine learning) that solve problems in the domains of genomics and molecular breeding.

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 Ph.D. in Mathematics, Computer Science, Engineering, or other quantitative discipline;
  • Experience applying sophisticated scientific methods for analysis, using statistical and mathematical programming languages such as Python, R;
  • Understanding of advanced analytics methods such as statistics, machine learning, and mathematical modeling;
  • Ability to turn complex data into predictive and prescriptive insights;
  • Experience analyzing and presenting complex data;
  • Proven problem-solving abilities;
  • Exceptional organizational, interpersonal, and written communication skills;
  • Ability to influence people at varying levels of responsibility.

Preferred Qualifications:

  • Knowledge of genomics, statistical genetics, or plant breeding;
  • Experience analyzing genetic/genomic data or applying computational techniques to biological data;
  • Experience with cloud computing technology;
  • Experience with several programming paradigms (e.g. object-oriented, functional, scripting);
  • Experience with Python, R, and Java languages;
  • Experience with command-line tools and scripting;
  • Strong publication record in scientific journals.
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