Plant Pathology Data Scientist

Universities of Wisconsin•Madison, WI

3d•$75,000 - $90,000•Hybrid

About The Position

The Department of Plant Pathology seeks a M.S. level Data Scientist to advance research in plant disease epidemiology, integrated disease management, disease forecasting, and agricultural economic modeling. This position will collaborate on faculty-led projects while leading the development of models, deployment to stakeholders via web interfaces, and evaluation and iteration of the tools.

Requirements

Demonstrated expertise in statistical modeling and machine learning
Experience with agricultural data management such as cleaning and analyzing large real-world agricultural datasets and developing and communicating results in presentations and publications
Demonstrated ability to communicate research findings through publications or technical reports
Proficiency in programming languages (Python, R) and data visualization
Master's Degree required; Plant Pathology, Agronomy, Applied Data Scientist, or a closely related field preferred

Nice To Haves

Prior involvement in interdisciplinary research teams such as National Predictive Modeling Tool initiative or other similar teams
Experience in deploying models for plant disease forecasting
Experience in agricultural economic modeling
Ph.D. preferred

Responsibilities

Design and implement data-driven models for plant disease epidemiology and forecasting.
Design and implement machine-learning techniques to address applied decision support
Work closely with faculty, graduate students, and interdisciplinary teams to integrate data science into experimental research.
Collaborate with software developers and extension specialists to translate models into practical tools for growers and stakeholders
Publish research findings in peer-reviewed journals.
Contribute to competitive grant proposals.
Develop reproducible workflows and data pipelines for large-scale agricultural datasets.
Maintain documentation and ensure compliance with data management best practices.
Documents approaches to address research questions and contributes to the establishment of reproducible research methodologies and analysis workflows
Independently identifies and implements appropriate data science techniques to find data patterns and answer research questions chosen by the lead researcher including data visualization, statistical analysis, machine learning, and data mining
Organizes and automates project steps for data preparation and analysis
Composes and assembles reproducible workflows and reports to clearly articulate patterns to researchers and/or administrators
Prepares data sets for analysis including cleaning/quality assurance, transformations, restructuring, and integration of multiple data sources