Our team uses historical patterns to predict potential future outcomes in a high dynamic and ambiguous scenario by filling gaps in available data through the application of several mathematical and statistician models supported by algorithms, leading to automated alarms and recommendation mechanisms.

 

Job Description:

  • Build solid statistical models through pattern recognition by using algorithms, mathematical tools, and other data science technics.
  • Identify transportation risks and ensure compliance through predictive and forecasting business models.
  • Manage and in-advance assess the probability of delays, correlated to several internal and external factors, including the cascade of events through different network nodes.
  • Scenario and simulation building to suggest solutions while facing identified risks.

 

Requirements:

  • Bachelor’s degree in Statistics, Mathematics, or Engineering.
  • Experience with statistical data treatment (R, Stata, Minitab).
  • Experience writing highly optimised, advanced SQL queries for large datasets.
  • Experience with Python.
  • Demonstrated ability to meet tight deadlines while managing multiple competing projects in a fast-paced environment
  • Demonstrated ability to influence and drive project deliverables
  • Strong business acumen
  • Advanced English skills.

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