Economist

Details: • Location: United States (Remote) • Schedule: Full-time, 40 hours per week • Contract: May 2026- April 2027 • Compensation: $65-70/hour (W2) We are partnering with a leading research and analytics team focused on understanding and forecasting U.S. labor market trends. This role sits at the intersection of economics, data science, and forecasting, with a strong emphasis on producing high-impact, data-driven insights. The ideal candidate will have a strong background in applied economics and experience building forecasting models, along with the ability to communicate findings clearly to both technical and non-technical audiences. Key Responsibilities • Develop, maintain, and enhance forecasting models for key labor market indicators • Analyze large-scale economic and proprietary datasets to identify trends and patterns • Partner cross-functionally with research, data science, editorial, and finance teams • Evaluate forecast accuracy and continuously improve model performance • Incorporate new data sources and methodologies into existing models • Translate complex analytical findings into clear, actionable insights • Contribute to written research, reports, and public-facing content • Summarize and interpret key U.S. labor market reports and economic indicators Required Qualifications • Master’s degree in Economics, Statistics, Data Science, or related quantitative field • 5+ years of professional experience in forecasting, econometrics, or time series modeling • Strong proficiency in R for data analysis, visualization, and forecasting • Experience working with large datasets and statistical modeling techniques • Familiarity with U.S. labor market data (e.g., BLS, Census, or similar sources) • Strong analytical thinking and problem-solving skills • Excellent written and verbal communication skills Preferred Qualifications • Experience with forecasting tools/packages such as forecast, fable, or tidymodels • Background in labor economics or macroeconomic analysis • Experience translating complex analyses into public-facing insights or reports • Exposure to machine learning approaches for forecasting