Principal Labor Market Data Scientist

UKG•,

21h•$150,500 - $214,500

About The Position

The Principal Labor Market Data Scientist is a senior individual contributor on UKG’s Go-to-Market Data Science team, which turns workforce data into insights for customers and business leaders. The role leads hands-on research and analysis of labor and workforce trends, from defining research questions and investigating data to validating results and explaining their significance. The position supports UKG senior leaders, Corporate Communications, and labor economists with evidence for executive discussions, media interviews, press releases, and thought leadership. It combines UKG workforce data with external labor market sources to develop timely insights, while applying sound methodological judgment about what the evidence supports. The role also provides technical leadership and mentorship to data scientists.

Requirements

Bachelor’s degree or higher in statistics, data science, economics, computer science, mathematics, or a related quantitative field.
8+ years of relevant experience in data science, applied statistics, quantitative research, or a related field, with ownership of complex analytical work and influence at a senior level.
Substantial recent hands-on experience analyzing labor market or workforce data, 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 independent work with large, complex datasets and building maintainable, reproducible analytical workflows.
Demonstrated ability to assess data quality and representativeness, reconcile inconsistent sources, and explain how methodological choices affect conclusions.
Ability to explain analytical findings, methods, and limitations clearly to technical and nontechnical colleagues and collaborate on business-audience materials.
Ability to lead ambiguous research assignments independently, collaborate with economists and technical partners, and deliver sound analysis under time-sensitive conditions.
Excellent written and verbal communication, including translating quantitative findings into concise, accurate materials for leaders, business audiences, or public use.

Nice To Haves

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.

Responsibilities

Partner with labor economists and Communications to define research questions and produce validated analyses, charts, and supporting materials for executive briefings, customer discussions, and media preparation.
Lead original research on hiring, separations, hours worked, wages, labor supply, and other workforce trends across industries, geographies, and workforce segments.
Deliver executive briefings, charts, talking points, and supporting analysis for customer discussions and media engagements.
Own analytical responses to urgent executive and media questions by clarifying the question, assessing feasibility, and delivering findings with relevant context and limitations.
Combine large-scale UKG workforce data with public and commercial labor data, evaluating source definitions, coverage, reporting lags, and comparability.
Develop and validate statistical methods for workforce indicators, trends, and comparisons, addressing 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.
Review the numerical accuracy and interpretation of findings, charts, and proposed public claims; explain uncertainty, challenge unsupported conclusions, and recommend further analysis when needed.
Partner with Product, Engineering, and data owners to resolve source issues and improve datasets; apply privacy protections and aggregation standards 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.