Biogeochemical Data Science Intern

About Pivot Bio:  

Fueled by an innovative drive and a deep understanding of the soil microbiome, Pivot Bio is pioneering game-changing advances in agriculture. Our products harness the power of naturally occurring microbes to provide nutrients to crops and new sustainable ways for farmers to reduce the usage of fertilizers as they work to help feed the world’s growing population.

Read/Hear more about Pivot Bio on Forbes or PBS News Hour. 

Position: Biogeochemical Data Science Intern 

Targeted Start Date: Summer 2023 

 Pivot Bio is developing microbial products that improve the nitrogen sustainability of agriculture by reducing the need for synthetic fertilizers. As a critical member of our Data Science / Computing team, the Biogeochemical Data Science Intern will help to bring together observational and experimental datasets to characterize sites that are suitable for specific field measurements. This will help Pivot Bio in future site selection for product testing, and ultimately in better understanding the influence of environmental factors on the performance of its microbial products. The internship will involve development of algorithms to munge, analyze, and visualize field data for characterizing measurement-specific suitability, and possibly include modeling environmental and management relationships with product performance as well.    

 Responsibilities:  

•  Develop statistical models and visualization tools to characterize sites that are suitable for specific nitrogen measurements.    
• Build and curate a repository of well-documented code and reproducible datasets.  
• Effectively communicate insights to both technical and non-technical collaborators and stakeholders.   

 Physical Demands: 

•  Job will involve mostly office and computer-based work  
• Repeating motions that may include the wrists, hands, or fingers 
• Sedentary work that primarily involves sitting/standing 
• Communicating with others to exchange information 

 Qualifications and Experience  

•  Masters or pursuing Ph.D. in a quantitative discipline, such as soil science, engineering, ecology, or computer science. Degrees with an emphasis in soil or agricultural sciences preferred.     
• Proficient in coding in R or Python, with a demonstrated ability to build organized, reproducible analytical workflows.  
• Expertise in Classification and Regression Trees (CART).  
• Experience with random forests, k-means clustering, and/or principal component analysis is a plus.  
• Experience using version control software (e.g. Git) and collaborative coding using Github preferred.  
• Strong communication and organizational skills.       

 *Must be authorized to work in the United States* 

 What we offer:  

•  Opportunity to gain professional experience in a progressive company  
• Exciting opportunity to work with a talented and fun team