Data Science - Econometrics

About

Bountiful is expanding our data science team with econometrics applications 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 econometric modeling needs. One includes developing price forecasting models using our proprietary data sets. The other is using our proprietary pricing data to create a price index. And lastly, develop a demand forecasting model using our proprietary shipment datasets. You will leverage your creativity and problem-solving skills to tackle our most pressing issues using an analytical lens. You will leverage market knowledge and analytical expertise to provide insights within our team by strengthening the core products and algorithms we build for our clients.

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:

• 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
• 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), applied mathematics, quantitative economics, quantitative finance or industrial engineering, or equivalent practitioner experience
• Relevant experience involving commodity/FX markets preferred as well as experience developing price forecasting or price-discovery analysis in agriculture commodities
• Experience writing clean, efficient Python code involving ETL processes, data manipulation, and standard data science packages (e.g., SciPy, NumPy, Pandas, SKlearn)
• Experience applying advanced analytical and statistical methods to solve business problems involving commodity markets
• Ability to explain nuances of commodity markets and complex analytical concepts to non-technical people from other fields
• Experience creating and implementing machine-learning models and dealing with large data sets (e.g., time series/econometrics models, 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 competing, quickly changing priorities

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!