Position Description: 

Tether is a data driven startup that optimizes the charging patterns of Electric Vehicles parked throughout a city, aggregating them into the world's largest virtual battery that reinforces the stability of the power grid. We are looking for candidates with a background in Operations Research (Mathematical Optimization) or Data Science who want to solve complex, multistep, decision making problems through constraint algorithms.  

The optimization algorithm lies at the core of Tether, which consists on the stochastic optimization of linear and non-linear systems of equations corresponding to vehicle arrival and departure times, electricity prices, and grid frequency data. This role consists on the development of a stochastic, constrained optimization model with risk aversion. Scenario variability and predictive modeling in Python, with knowledge of the Pyomo optimization framework, is preferred.

We want candidates that are impact driven, looking for a dynamic and collaborative work environment, and are interested in helping to develop the optimization algorithm at the hart of the company.

Keywords: #Python, #Pyomo, #Optimization, #MINLP, #OR, #Stochastic