The Research Economist is responsible for analyzing complex labor market data to provide actionable insights that drive policy formulation and strategic business decisions. This role combines deep expertise in econometrics with a practical mindset, working closely with strategy, policy, and research teams to understand workforce dynamics, wage trends, and employment drivers. The Research Economist will leverage advanced econometric models (regression, time series), clustering techniques, and machine learning to uncover structural trends and guide decision-making regarding the labor market
Key Responsibilities:
- Analyze large-scale labor market datasets to identify employment trends, skills gaps, and workforce segmentation, supporting initiatives to improve labor participation and productivity.
- Develop and refine rigorous econometric models (e.g., multivariate regression, panel data analysis) to isolate variables impacting wages, hiring rates, and job retention.
- Utilize advanced time-series techniques (e.g., ARIMA, VAR) to forecast key labor indicators such as unemployment rates, labor demand, and sector-specific growth.
- Apply clustering algorithms to segment the workforce and business entities, identifying distinct behavioral groups to tailor programs and policy interventions effectively.
- Design frameworks using causal inference methods (e.g., Difference-in-Differences, Propensity Score Matching) to measure the actual impact of labor policies and interventions.
- Create and maintain automated workflows to track key economic indicators (e.g., Saudization rates, female participation), ensuring alignment with national and organizational goals.
- Present complex economic findings in a clear, visual manner to stakeholders, translating statistical outputs into strategic narratives for non-technical audiences.
- Stay updated with the latest advancements in computational economics and data science, driving the adoption of new analytical tools and best practices within the team.
Required Skills & Qualifications:
- Bachelor's degree in Statistics, Economics, Econometrics, Quantitative Finance, Mathematics, Physics, or a related field.
- 4+ years of experience in data science, economic research, or quantitative analytics. A specific focus on labor economics, policy evaluation, industrial organization, or applied econometrics is highly desirable.
- Econometrics & Statistical Modeling.
- Strong proficiency in time-series analysis (ARIMA, GARCH, Vector Autoregression) to model seasonality and trends in economic data.
- Experience applying unsupervised learning techniques (K-Means, Hierarchical Clustering) and supervised learning to labor data for segmentation and classification.
- Advanced proficiency in Python, R, or Julia for statistical analysis. SQL is a must for data extraction.
- Deep understanding of labor market theories, including supply and demand elasticity, human capital theory, and workforce dynamics.
- Data Visualization & Storytelling.
