We are actively seeking a SENIOR DATA SCIENTIST to join our rapidly growing Research and Development Department. The successful candidate will be responsible for developing and implementing models enabling field experimental design and optimization of product performance across testing environments. This person will work closely with Benson Hill data engineers, scientists and project leaders to maximize the impact of Benson Hill’s product development programs.
(ESSENTIAL DUTIES AND RESPONSIBILITIES)
- Develop and refine data analysis, storage, and modeling systems.
- Conduct independent analyses of performance, and use advanced approaches to identify predictive models in a geospatial framework.
- Participate in the design of hypothesis-driven experiments and analyses.
- Perform spatial and statistical analysis on experimental outputs and interpret results
- Communicate results in written and visual formats to scientists and program leaders.
- Identify opportunities for model enhancements and opportunities for new models to create value in the product discovery and testing pipeline.
- PhD preferred (minimum BS plus 4 years’ experience), in applied mathematics, physics, engineering, statistics, ecology, or closely related field with formal training in statistics and experimental design, with demonstrable track record of peer-reviewed publications.
- Demonstrated enthusiasm for data-driven discovery.
- Experience with geospatial analyses, modeling, and interactive system development.
- Highly developed ability to identify and evaluate predictive models and their utility.
- Experience with machine learning and statistical concepts, packages and libraries.
- Background and experience analyzing data with Python, R, or Julia.
- Expert with at least one scripting language, Python or R preferred.
- Ability to work in collaborative team, and the ability to respond positively to critiques of work.
- Excellent communication skills, both electronic and in-person.
- A track record of producing deliverables and meeting tight release deadlines.
- Ability to work autonomously, identify key tasks, and find solutions to challenges.
- Experience organizing and planning complex projects
- Strong record of personal development and learning new technologies.
- Strong understanding of scientific concepts, approaches, application, and interpretation.
- Demonstrated experience with common machine learning approaches, statistics, geospatial and command line (e.g. R) applications.
- Doctorate in associated area, with proven publication and communication track record.
- Familiarity with crop science and agronomic applications and modeling a plus.
- Background and experience using AWS or experience with other cloud architectures
- Attention to detail
- Strong Customer Focus
- Ability to focus and work independently with little direction