Collaborate with data scientists/engineers/stewards on data extraction and data cleaning.
Develop powerful analytics insights from geographical, manufacturing, industrial data using advanced machine learning techniques.
Design, implement and optimize OR/simulation/machine learning models based on structured and unstructured data.
Work closely with the software engineering team in the delivery of analytic software
Work in a highly interactive, team-oriented environment.
PhD in Mathematics, Economics, Statistics, Operations Research or a related field with statistics courses/publications/proven expertise (Electrical/Mechanical/Environmental Engineering, Spatial Statistics, Geoinformatics, Environmental Modeling, Engineering, Computer Science, or Computational Biology)
Proficient in machine learning algorithms and concepts;
Ability to work in a highly interactive, team-oriented environment.
Comfort in communicating technical content in an easy to understand way
Proficiency of at least one of Python or R is a must-have and working knowledge of the other
Proficiency in Spatial and/or Temporal Statistical Modeling
Proficiency in Machine learning algorithms and concepts (Ensembles, Deep Learning, SVM, etc.)
Experience working with agricultural/biological scientific data is highly desired
Drive for translating business problems into research initiatives that deliver business value
Creativity in defining challenging exploratory projects