Econometric Modeler
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Econometric Modeler
Ref No.: 18-00227
Location: Washington, District of Columbia
We have a new position that just opened at the IMF that we are trying to fill, an Econometric Modeler.
They are looking for a candidate with a PhD in Applied Mathematics or Computer Science who knows statistical learning, the merging of machine learning and econometrics.
Strong programming experience ideally in C# and Python.
Strong theoretical machine learning as well as probability and statistics.
Candidate must work onsite in Washington, DC.


Machine Learning Econometric Modeler

Qualifications:
The successful candidate should be close to graduation or already possess a PhD in applied mathematics, computer science or related disciplines.

Knowledge:
Theoretical and Practical knowledge in Machine Learning and correlation to Statistics.
Statistical learning.
Strong programming skills (Python, C#, R or Matlab)
Expert knowledge of numerical integration and numerical methods for solving large scale linear and nonlinear systems

Ability:
Implement Machine Learning models and algorithms.
Ability to train or teach Economist regarding how Machine Learning can be utilized for specialized topics.
Ability to find innovative solutions to unusual problems.
Ability to follow up current academic research on quantitative finance, computational economics, statistics, and econometrics.

Background:
The successful candidate will serve as a member of the Economic Modeling Support Team, and work on quantitative finance modeling, being required to implement financial models and numerical algorithms using, several programming languages.
This position requires advanced programming skills and a strong background in applied mathematics and computer science.
The successful candidate should have extensive knowledge of numerical methods, computational methodologies, high performance parallel computing and algorithm development and optimization.
Familiarity with quantitative finance would be a plus.