Location: Indianapolis, IN
Advanced Agrilytics (“Company”) is an agronomic services 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 agronomic, soil and environmental data we collect on our customer’s enterprises. 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.
Scientists at Advanced Agrilytics are expected to develop and help support new techniques to address quantitative problems in digital agriculture using large datasets.
- Data mining using state-of-the-art methods on large spatio-temporal datasets derived from agricultural production systems.
- Extending data resources with third party sources of information when needed.
- Proposing new ideas and novel solutions that do not follow conventional thinking or approaches.
- Work closely with software engineers to deploy solutions to problems in a production environment
- Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.
- Establish procedures for the application of basic machine learning algorithms to agronomic and environmental data.
- Completed a M.S. or PhD in a quantitative field with a minimum of three years of professional work experience
- Strong background in statistics methodology and the ability to infer causal relationships
- Strong hands-on proficiency with at least one data science programming language (R, Python, Julia)
- Experience with machine learning (ML) and artificial intelligence (AI) algorithms.
- Strong research track record
- Experience in working with large-scale spatial and temporal data
- Experience with data visualization
- Ability to work in a fast-paced business environment.
- Experience with ArcGIS or other geographic information systems (GIS) platform would be beneficial
- Are a self-starter who can own complex projects from start to finish