Indigo is a company dedicated to harnessing nature to help farmers sustainably feed the planet. With a vision of creating a world where farming is an economically desirable and accessible profession, Indigo works alongside its growers to apply natural approaches, conserve resources for future generations, and grow healthy food for all. Utilizing beneficial plant microbes to improve crop health and productivity, Indigo’s portfolio is focused on cotton, wheat, barley, corn, soybeans, and rice. The company, founded by Flagship Pioneering, is headquartered in Boston, MA, with additional offices in Memphis, TN, Research Triangle Park, NC, Sydney, Australia, Buenos Aires, Argentina, and São Paulo, Brazil. www.indigoag.com

Outcomes:

• Lead requirements gathering for Indigo optimization solutions 
• Develop and implement complex mathematical and statistical models that relate logistics and marketplace activities to financial results 
• Understand all of the parameters involved in the optimization for Indigo's logistics and marketplace project
• Be able to identify the scope and complexity of the project (linear / non-linear) as well as the solvers necessary for implementing the v2.0 optimization problem and identify data required to facilitate solving logistics and marketplace problem space
• Build v2.0 prototype for delivery optimization of all crops
• Bring data science up to speed with additional applications of optimization solutions and work together with data science to expand operations research into other potential avenues of interest
• Serve as company’s foremost expert on logistics optimization 
  

Competencies:

• Strong skills in two of: R, Python, C++, Java
• Fluent with the leading MIP/LP Solvers (CPLEX, Gurobi, XPRESS, AMPL) in the industry as well as out of the box/ self-coded solutions
• Able to translate a business problem into the appropriate mathematical program
• Strong communication skills with ability to work with a variety of stakeholders
• Able to work independently and drive to a solutions with minimal direction
• Comfortable with ambiguity and challenging company goals
• Able to work in an extremely fast-paced environment with changing priorities
• Able to prioritize delivering business value relative and able to discuss trade-offs between time to implement and quality of the solution
• Able to think at scale (solving these problems over a larger domain space versus a narrow implementation)
• Able to focus on results and not the process to get there … willing to “throw something away” if needed
• Able to partner closely with software development to turn data science products into best-in-class end-user applications
• Able to set time expectations for work and communicate the scope of the project clearly to stakeholders (data science, engineering + executive management)
• Able to lucidly break down optimization ideas for a non-expert audience.
• Able to translate work in research and optimization to provide innovative approaches to analyze/interpret and take action on observational as well as trial field data
  

Qualifications:

• Academic background in applied mathematics, operations research, machine learning, computer science or related field, advanced degree preferred
• 5-10 years of simulation and/or optimization experience, including implementation beyond prototypes
• Requisite coding skills for linear and non-linear optimization
• Experience in Linear Programming, Mixed Integer Programming, Nonlinear Optimization, Combinatorial Optimization
  
• Experience working with NP-hard problems and supporting heuristics/algorithms