Indigo: Operations Research Scientist
500 Rutherford Ave, Suite 201
Boston, MA 02129

Employee Testimonials

Jesse Deardorff
Cassandra Ball
Trudi Baker

Video

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 companys 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 CNBCs 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 So 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!

Responsibilities:

  • Partner with stakeholders to gain a thorough understanding of our main businesses and evangelize the role OR plays in helping us achieve Indigos mission
  • Grounded in a solid scientific approach and a continuous improvement mindset, research and identify opportunities for optimization across Indigos 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 Indigos mission and establish, with minor guidance, ambitious (but achievable) quarterly goals

Competencies:

  • 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

Qualifications:

  • 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.

#LI-BS1

Full-time

Employee Testimonials

Jesse Deardorff
Jesse Deardorff

Our plan is focused on the growers and helping them achieve maximum profitability using a unique set of tools. On top of offering a dynamic product, developing relationships and partnerships with growers will be key to achieving our goals.

Cassandra Ball
Cassandra Ball

I love the lab culture of Indigo. It's great being surrounded by both hard-working and fun-loving people. Most of our experiments are challenging and having the support of coworkers throughout the day really makes it fun for me.

Trudi Baker
Trudi Baker

From the early days when the whole company consisted of less than 20 people, I remember EVERYONE would gather for lively brainstorming sessions, the founder of the company, bench scientists, data scientists, lab techs, an attorney - everyone participated and listened and learned from each other's experiences and opinions. Today Indigo is much larger, but this spirit of open communication and collaboration is still strong. We collaborate through our everyday work, through software like our online innovation exchange where we bounce ideas off each other, and through "hands-on" brainstorming sessions where we learn a new assay and some of the points which are most challenging and can share ideas about how to make it more efficient.