Data Engineer Co-Op
BayerUpdate time: September 22,2020
Job Description

In Bayer’s Crop Science division, we shape agriculture through breakthrough innovation that helps to nourish our growing world, preserve natural resources and deliver better solutions for all farmers. Using the creative spark that comes from human ingenuity, we seek to deliver world-class innovation, set new standards in sustainability, and drive our digital transformation. Our products include high-performance seeds & traits, crop protection solutions, and digital farming tools.

 

YOUR TASKS AND RESPONSIBILITIES

 

The primary responsibilities of this role, Data Engineer Co-Op, are to: 

 

  • Integrate, transform, validate and reconcile large amounts of data;
  • Assemble and evaluate data such that new insights, solutions and visualizations can be derived;
  • Support the exploratory data analysis, data cleaning and processing;
  • Perform data discoveries to understand data formats, source systems, file sizes and engage with business partners in this discovery process;
  • Identify trends, data quality issues, anomalies across large data sets, particularly in the area of machine data and other agronomic management practices;
  • Be accountable for and ensure solutions meet business requirements;
  • Write robust and well-documented research code;
  • Engage with diverse research groups to understand their models and products and develop solutions to meet their data needs.

 

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 in a Bachelor’s degree with a focus in Math, Statistics, Information’s Systems Management, Computer Science or Geographic Information Systems(GIS);
  • Development experience with recent experience in Python, R and SQL;
  • Experience with working with geospatial datasets/GIS;
  • Experience working with cloud tools such as AWS and Domino data science platform;
  • Demonstrated experience with global multi-disciplinary teams and learning the science;
  • Creative, proactive, bold and out-of-box thinking.

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