Data Scientist - Soil & Plant Sciences

DuPont has a rich history of scientific discovery that has enabledcountless innovations and today, we're looking for more people, in more places,to collaborate with us to make life the best that it can be. The Environmentand Ag Systems Data Science team focuses on bringing data and analyticssolutions to farmers by exploring the interactions between crops, environment,and management. We are looking for individuals with a desire to help farmers,familiarity with geospatial or other high dimensional data and an aptitude foranalytics, machine learning and data science.
Job Duties/Responsibilities:
Join a team of domain scientists, data scientist, and engineers assembled to identify business problems, provide data driven solutions, and deliver production applications which enhance our customer's decision process.
Identify, acquire, and engineer feature data sets with potential to address customer needs.
Apply machine learning, statistical or mechanistic models and other computational approaches to extract insights from large datasets in agronomic systems.
Develop, prototype, and implement software solutions with engineering and production teams.
Collaborate with scientists from multiple domains in solution/experiment design and analyses.
Conduct and communicate results of research on data science approaches to improve decisions, add value to services, extend or improve in-house models and algorithms, and contribute to the advancement of these ideas into the marketplace.
Uphold DuPont Core Values at all times.
Educational Qualifications:
PhD in Computer science, Engineering,Statistics, Physics or a related field. Or, a PhD and demonstrated experience withquantitative applications in Soil, Hydrology, Agronomy/Plant Sciences,Geography, Ecology, Climatology or related fields. 2-4 years of relevantpost-graduate work experience required.
Competencies & Experience Desired:
Outstanding problem solving skills and a proven ability to independently deliver analytic solutions by asking the right questions, identifying necessary data sources, building predictive models, and producing actionable results.
Expertise in machine learning, data mining, statistical methodology, or simulation modeling and demonstrated experience using these techniques to solve research problems.
Proficiency in Python or R.
Geospatial and remote sensing data experience desired.
Familiarity with cloud based systems.
Experience with Relational or NoSQL databases.
Proven ability to work in a team setting and ability to lead teams to complete complex projects on time and in budget.
Superior communication skills, both verbal and written.
Familiaritywith farming and/or precision agriculture strongly preferred, but not required.

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