Data Scientist – Applied Research
Location: Indianapolis, IN
Advanced Agrilytics (“Company”) is an agronomicservices company enabled by best in class digital capabilities providing growers independent, sophisticated and robust input prescriptions and operational advice. The company has focused on the major inputs and in-crop decisions as determined by value and return on investment within the overall system. This company is well differentiated from the crowded SaaS providers in the digital ag space given its impressive multi-season results and independent, high-touch business model.
We are seeking a Data Scientist to extract insights from the research trials and data we collect for various internal and external projects. As part of the Advanced Agrilytics data science team, your focus will be to develop quantitative solutions to help growers increase crop yields and reduce yield variation.
- Analyze data from agricultural research trials for internal and external stakeholders
- Conduct studies to learn from our vast amount of data, including exploratory data analysis, observational and environmental data.
- Use R, Python or Julia to interact with large datasets and conduct complex data processing
- Use data visualization tools (i.e., Tableau)
- Work closely with our field research team, software engineers and key stakeholders to disseminate results.
- Completed a M.S. or PhD in a quantitative field with at least one year of professional work experience
- Strong hands-on proficiency with at least one data science programming language (R, Python, Julia)
- Experience in working with large-scale spatial and temporal data
- Experience with data visualization
- Experience with ArcGIS or other geographic information systems (GIS) platform would be beneficial
- You have good applied statistics skills, such as distributions, statistical testing, regression, etc.
- You are comfortable digging into new problem domains, applying a wide variety of tools/techniques for diverse efforts.
- You communicate well with internal and external stakeholders
- You are able to turn data findings into actionable insights that can help direct internal modeling efforts as well as provide product efficacy guidance to external stakeholders
- You are a self-starter who can own complex projects from start to finish
- Work quickly and accurately under time pressure