What if nature could be harnessed to help farmers sustainably feed the planet? Since 2014, Indigo has questioned agriculture's full value chain to improve grower profitability, environmental sustainability, and consumer health. The company’s scientific discoveries and digital innovations have amplified new value from soil to sale, benefiting more than 10,000 growers to date. Indigo is also the company behind The Terraton Initiative, a global effort to draw down one trillion tons of atmospheric carbon dioxide by unlocking the potential of agricultural soils. In 2019, Indigo was ranked #1 on CNBC’s Disruptor 50 list. Headquartered in Boston, MA, Indigo has additional offices in Memphis, TN; Research Triangle Park, NC; Sydney, Australia; Buenos Aires, Argentina; Basel, Switzerland; and São Paulo, Brazil.
As part of the Operations Research Team at Indigo, you will be leveraging data, optimization algorithms, and machine learning to help solve Indigo's toughest logistics challenges and drive profitability. How do we match grower offers and buyer bids in our marketplace to maximize transaction volume? How do we assemble efficient truck routes that reduce our transportation costs when delivering grain? How should we sequence visits to farmers in order to reduce sample collection times? Where should we station agronomists in order to reduce their travel times and maximize coverage? You'll have the chance to expand your analytics skills while working on cool and impactful business problems!
- Partner with stakeholders to gain a thorough understanding of our main businesses and evangelize the role OR plays in helping us achieve Indigo’s mission
- Grounded in a solid scientific approach and a continuous improvement mindset, research and identify opportunities for optimization across Indigo’s business units
- Earn the trust of peers and project stakeholders by developing and implementing complex optimization/ML models and algorithms that result in actionable business insights and/or drive our products
- Develop and execute on a research agenda that is consistent with Indigo’s mission and establish, with minor guidance, ambitious (but achievable) quarterly goals
- Deep understanding and knowledge of at least one OR core discipline (e.g., linear programming, combinatorial optimization, network flows, dynamic programming, stochastic models, machine learning) as well as good breadth and working knowledge of three or more
- High competency in at least one statistical computing language (Python – strongly preferred, R, Julia) and one high-performance object-oriented language (Java, C++)
- Working knowledge of SQL and popular data science libraries (e.g., scikit-learn, tidyverse, R Shiny, TensorFlow)
- Some knowledge of full-stack web development, as well as the ability and desire to quickly acquire new software skills as needed
- Ability to simplify and model the most relevant tradeoffs in a complex and loosely stated business problem, translating it into a tractable mathematical program
- Strong communication skills. Ability to partner and earn the trust of a variety of stakeholders and audiences, including project managers, software engineers, business analysts, and executives to gather requirements and understand business context
- Thrives in a fast-paced growth environment; comfortable with ambiguity, projects with uncertain outcomes, and shifting goals. Excellent prioritization skills and bias for action. Delivers business value early and often, while managing stakeholder expectations
- Methodical in their thinking. Follows a scientific process and writes code and documents results in a way that guarantees archival value and reproducibility. Uses collaboration tools (Git, Confluence, Jira) effectively for this purpose
- Ability to think big and come up with solutions and implementations that work at scale
- PhD (strongly preferred) in operations research, computer science, engineering, statistics or other related disciplines, or MS with 3+ years of industrial R&D experience in these areas
- 5+ years of experience using mathematical modeling, optimization, machine learning, and simulation to solve complex resource allocation problems
- Demonstrated experience solving NP-hard problems and developing effective algorithms and heuristics
- 3+ years of experience writing software in at least two of the following: Python, R, Java, and C++. Working knowledge of SQL and popular data science libraries (e.g., scikit-learn, matplotlib, tidyverse, R Shiny, TensorFlow, etc.). Some full-stack web development experience preferred
- Experience solving large problems with at least one MILP solver package and/or modeling language (CPLEX, Gurobi, XPRESS, AMPL)
Indigo is committed to living our values, specifically “creating a work environment where everyone feels respected, connected, and has opportunities to learn and grow.” As part of living our values, we strive to create a diverse and inclusive work environment where everyone feels they can be themselves and has an equal opportunity of succeeding.