Back to jobsProven experience developing, refining, and monitoring machine learning models.
Substantial experience querying, cleaning, compiling, and analyzing big data.
Familiarity applying various computational social science methods including data mining, data visualization, natural language processing, text analysis, and basic time series forecasting and machine learning models.
Familiarity with scenario analysis/stress-testing, simulation analysis, rare event modeling, and stochastic modeling preferred but not required.
Substantial experience with Python, especially data-science-relevant libraries (e.g., numpy, pandas, scikit-learn, etc.).
Familiarity with database management tools and techniques (e.g., SQL, S3, API protocols) preferred but not required.
Understanding of model evaluation methods and metrics.
Ability to operationalize non-technical ideas into relevant research designs, features, and model outputs.
Experience translating code between languages (primarily R to Python)
Comfort working with legacy codebase
Experience writing production code, not just notebooks
