What are the responsibilities and job description for the Research Scientist position at Gro Intelligence?
Research Scientists at Gro translate business priorities into short- and long-term research deliverables of state-of-the-art methods and their applications in spatiotemporal data science, natural language processing, agricultural, climatological, and economic systems science, and complexity science. They specialize in the development and application of machine learning (ML; including Deep Learning, DL) and artificial intelligence (AI) to understand and forecast the behavior of complex systems and de-risk the application of novel technologies to maximize impact toward improving food security. Research Scientists at Gro aim to deliver new innovations, operational efficiencies, and technical concepts to internal teams, while the collective needs of external customers help guide research priorities.
What You'll Do
- Initiate the design, development, execution and implementation of technology research projects with a focus on geospatial analytics, including but not limited to land use classification, weather or earth system emulation and forecasting, and data assimilation.
- Conclusively evaluate the applicability of scientific advances, particularly those in machine learning and artificial intelligence to meet business needs.
- Identify promising technical approaches, and implement and test proofs-of-concepts to advance improved processes and technologies through to development and production for use by other teams.
- Provide internal consultation and strategic thought leadership as they pertain to technical solutions in ML (including DL) for geospatial applications and spatiotemporal analytics.
- Maintain substantial knowledge of state-of-the-art principles and theories, and provide industry intellectual leadership for artificial intelligence in agriculture.
- Identify new avenues of research by interacting with collaborators, assess required timelines and resources required, and help develop long-term research strategy.
What We're Looking For
- A demonstrated record of capabilities in formulating research projects, executing said projects, and communicating their results and impact to stakeholders.
- Comfort in navigating ambiguous, complex, evolving environments with significant autonomy.
- Ph.D. or 5 years of domain expertise in artificial intelligence (including machine learning) in geospatial and spatiotemporal analytics as they apply to disciplines like agricultural, ecological, earth, and/or climate systems.
- Theoretical and applied experience with programmatic processing of geospatial data and common data structures like tensors, including reprojection and set operations with tools similar to GeoPandas and rioxarray.
- Data science and ML engineering experience to implement and test new algorithms, methods, and frameworks, preferably with a high level of competency in Python and experience with at least one ML framework like PyTorch.
- Capability to temporarily flex into Data Scientist or ML Engineer roles as business needs demand.
- An impact-first mindset with focus on driving outcomes by graduating research deliverables to development and production.
- Motivation and fortitude to work on solutions to society’s grand challenges, namely food security and climate change.
Nice to Have
- Interest in developing systems science to relate food systems, climate change, and operations research to improve global food security.
- Experience in applications and theory of explainable AI (XAI) and the interrelationships between explicitly implemented dynamical systems models and machine learned models.
- Cloud engineering or MLOps experience for scaling ML workflows.
Compensation
The salary range for this role is expected to be $120,000 - $150,000. Other compensation for the role includes equity, a generous PTO policy and health, vision & dental insurance.
Salary : $120,000 - $150,000