Principal Labor Market Data Scientist

Partner with Communications, the CEO's office, and labor economists to set research priorities and develop evidence-based narratives. Deliver executive briefings, charts, talking points, and supporting analysis for customer discussions and media engagements. Lead original research on hiring, separations, hours worked, wages, labor supply, and other workforce trends. Identify questions that matter to employers and workers, and investigate changes across industries, geographies, and workforce segments. Own the analytical response to urgent executive and media questions. Clarify the question, assess feasibility, and deliver findings with the context and limitations needed to use them accurately. Combine large-scale UKG workforce data with public and commercial labor data. Evaluate source definitions, coverage, reporting lags, and comparability before drawing conclusions. Develop and validate statistical methods for workforce indicators, trends, and comparisons. Address seasonality, changing employer populations, missing data, revisions, and sampling bias. Distinguish workforce changes from data artifacts and association from causation. Build reproducible analysis and recurring reporting workflows using SQL and Python. Maintain documented methods, versioned code, and automated checks so results can be reproduced, reviewed, and updated efficiently. Review the numerical accuracy and interpretation of findings, charts, and proposed public claims. Explain uncertainty, challenge unsupported conclusions, and recommend when findings need further analysis before use. Partner with Product, Engineering, and data owners to resolve source issues and improve the datasets supporting workforce insights. Apply appropriate privacy protections and aggregation standards in collaboration with Legal and privacy teams. Provide technical leadership and mentor data scientists through research design, code review, and stakeholder discussions. Lead substantial workstreams independently and communicate priorities, tradeoffs, and delivery risks clearly. Bachelor's degree in statistics, data science, economics, computer science, mathematics, or a related quantitative field, with substantial relevant professional experience. 8+ years of relevant experience in data science, applied statistics, quantitative research, or a related field, with demonstrated ownership of complex analytical work and influence at a senior level. Substantial hands-on experience analyzing labor market or workforce data in recent professional roles, including producing research, indicators, or insights from employment, payroll, wage, hours, job posting, or worker-level datasets. Deep applied statistical expertise, including time-series analysis, sampling and weighting, hypothesis testing, and uncertainty estimation. Ability to select methods appropriate to the data and question. Strong SQL and Python skills, including the ability to work independently with large, complex datasets and build maintainable, reproducible analytical workflows. Demonstrated ability to assess data quality and representativeness, reconcile inconsistent sources, and explain how methodological choices affect conclusions. Excellent written and verbal communication, with experience translating quantitative findings into concise, accurate materials for executives, business audiences, or public use. Ability to lead ambiguous research assignments independently, collaborate with economists and technical partners, and deliver sound analysis under time-sensitive conditions. Master's or PhD in a relevant quantitative discipline. Recent experience developing labor market research, indicators, or data products at a statistical agency, payroll provider, workforce analytics organization, or comparable research institution. Experience supporting corporate communications, economic publications, executive briefings, or media preparation, including reviewing research for public release. Experience with econometrics, forecasting, or causal inference applied to labor and workforce questions. Experience with Google Cloud Platform and BigQuery, workforce management or human capital management data, and recurring labor market indicators or benchmark publications.