Our data scientist will be in charge of developing mathematical models to predict and improves operational efficiency. 


  • Help out building models to improve distribution and placing of scooters
  • Develop micro models for different areas to help connect priorities of these areas to our main growth model
  • Roll out logic (or algorithms) to software to improve customer experience to users, chargers and Grin Fields users
  • Help forecasting and predicting questions on baselines of key metrics (rides per day, active scooters, rides per scooter, distribution coefficients of operations zones, etc)

Table stakes:

  • Expert coding in R or python
  • Experience with SQL
  • Experience with feature engineering and machine learning
  • Experience working with API to connect, extract, gather and analyze data
  • General Statistics Knowledge:
    • Understands hypothesis testing (p-value)
    • Understanding of key stat concepts like: mode, mean, standard deviation, statistical distribution types, discrete vs continuous variables, Bayes Theorem, Type i and Type ii errors,
    • Advanced Stats: K-Neighborhood algorithm, decision tree learning, T-tests, Markov chains
  • Can describe a metric in terms of inputs and outputs
  • Attention to detail
  • Self organized
  • His/her data interpretation goes beyond the obvious
  • Problem solver
  • Shows hunger to learn new skills & tools to solve problems

Nice to haves:

  • Previous experience building dashboards on tools like Superset, ModeAnalytics, Periscope or any other viz tools based on SQL
  • Can run a data product on the cloud
  • Master in SQL

Special spikes:

  • Has done a project with PostGIS
  • Can define tasks and timelines of a project
  • Has created the data structure for a previous project or company
  • Led an experiment using bayesian testing in a previous company

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