Early Career Data Scientist/Economist

Candidates should possess deep expertise in economics and applied data science, with the ability to frame business questions into analytical or modeling problems. A graduate-level research background in data-intensive issues or at least one year of industry experience in machine learning or economics-focused roles is required. Essential skills include a blend of economic theory, applied econometrics, and business acumen, along with proven ability to identify and measure causal business impacts using appropriate statistical techniques, particularly in complex or observational settings. Strong engineering skills in R or Python, fluency in data manipulation (SQL, Pandas), and machine learning tools (scikit-learn, XGBoost, Keras/Tensorflow) are necessary. The ideal candidate must also demonstrate an ability to identify and prioritize high-impact problems, deliver solutions with appropriate trade-offs between urgency and quality, and possess strong verbal and written communication skills to effectively convey complex findings to diverse audiences. Prior full-time experience is a plus.