Spatial Data Science

About

Bountiful is looking for a talented data scientist with a geospatial focus in providing analytics to the agriculture sector. Bountiful brings yield forecasts and analytics to specialty crops using satellite imagery, weather, geographical, and historical data sets. Using a data-agnostic approach, we leverage private and public data sets in conjunction with the latest machine learning techniques to provide actionable information to the grape, almond, and walnut agriculture industries.

Bountiful is an agile team whose goal is to use the latest analytical methods, incubate new technologies and drive innovative ways to develop new opportunities to make a significant and lasting impact.

Bountiful clients include farmers, agribusiness, and specialty crop investment groups.

Your Role

There are several specific areas of our product that have spatial data science needs. One includes improving our GIS pipeline and revamping our ETL process. A second need is computer vision to improve the accuracy of field level crop location, new plantings and pull outs. Lastly, there is a need for anomaly detection in satellite imagery and weather data to improve outlier flagging. You will leverage your creativity and problem-solving skills to tackle our most pressing issues using an analytical lens.

You will provide direct impact to some of the largest organizations in the agribusiness and consumer foods sectors. This role will be part of the data science team at Bountiful. Specifically, leading research and development projects and developing those into full-fledged aspects of the product.

Main tasks include:

• Review and improve satellite imagery processing
• Improve our spatial data science pipelines
• Develop new tools for crop identification
• Improve anomaly detection
• Develop field level variability forecasting models
• Research new geospatial datasets in optical and radar domains
• Directly interfacing with the data science lead
• Communicating results/progress succinctly with stakeholders in the company & outside of the company document progress
• Keeping code in version control and keep well documented/commented code
• Contributing to weekly/daily team meetings
• Considering first principle decision-making

Qualifications

• Undergraduate degree and excellent academic record
• MSc or Ph.D. level degree in a quantitative discipline such as computer science (especially Machine Learning), physics, applied mathematics, spatial data science, or equivalent practitioner experience
• Relevant experience involving geospatial analysis, computer vision, remote sensing, agricultural or large geospatial data sets
• Experience with GIS software/libraries such as QGIS, ESRI, Google Earth Engine (GEE), PostGIS, GeoPandas,
• Experience writing clean, efficient Python code involving ETL processes, data manipulation, and standard data science packages (e.g., SciPy, NumPy, Pandas, SKlearn, TensorFlow)
• Experience applying advanced analytical and statistical methods to solve business problems involving commodity markets
• Ability to explain nuances of spatial data science to non-technical people from other fields
• Experience creating and implementing machine-learning models and dealing with large data sets (e.g., time series linear models with regularization algorithm, classification algorithms like random forest, support vector machine, or LGBM)
• Experience working with production level IDEs (e.g., Visual Studio, PyCharm), interactive IDEs (e.g., Spyder, Jupyter), and Version Control(e.g., git, svn)
• Creative, naturally curious, and willing to take intellectual risks
• Comfortable working under high stress environments
• Familiar with AWS products such as EC2, S3, Lambda, CloudWatch

Must have a passion for agriculture and improving lives in general. If you want to make a positive and lasting impact on the world, we want you on our team!