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Advisor, Workforce Reporting & Insights

Job in Bartlesville, Washington County, Oklahoma, 74005, USA
Listing for: Phillips 66
Full Time position
Listed on 2026-10-05
Job specializations:
  • IT/Tech
    Business Intelligence, Data Analyst
Salary/Wage Range or Industry Benchmark: 125000 - 153000 USD Yearly USD 125000.00 153000.00 YEAR
Job Description & How to Apply Below

Phillips 66 & YOU
- Together we can fuel the future

The Advisor, Workforce Reporting & Insights designs, develops, and delivers workforce analytics, reporting, and decision-support solutions that help Human Resources and business leaders make informed people and business decisions. This role combines workforce analytics expertise with data science, business consulting, and data storytelling capabilities.

The Advisor serves as a trusted analytical consultant: clarifying business questions, identifying the right data and methods, developing rigorous analyses, translating findings into practical recommendations, and helping stakeholders act on the results. The role also stewards workforce reporting products, metrics, data quality, and self-service capabilities across multiple HR data sources.

Position can be based in Bartlesville, Oklahoma, or Houston, Texas.

What You’ll Do Business consulting and insight development
  • - Partner with HR, business, and functional leaders to understand strategic priorities, frame ambiguous workforce questions, define measurable outcomes, and translate business problems into hypotheses, analytical plans, decision criteria, and clear deliverables.
  • - Lead analytical engagements from intake and scoping through analysis, recommendation, delivery, and follow-up.
  • - Advise stakeholders on appropriate metrics, analytical approaches, data limitations, and interpretation of results.
  • - Develop recommendations that connect workforce findings to business implications, including talent supply, workforce composition, retention, mobility, hiring, capability needs, organizational effectiveness, and other workforce priorities.
  • - Build trusted relationships with stakeholders and manage expectations regarding scope, timing, data availability, and level of confidence in findings.
Data science and advanced analytics
  • - Apply descriptive, diagnostic, predictive, and prescriptive analytical methods to workforce and business data, selecting approaches appropriate to the business question.
  • - Clean, integrate, transform, and validate structured and unstructured data from HR systems, surveys, enterprise data sources, and relevant external sources.
  • - Use statistical methods such as trend analysis, segmentation, correlation, hypothesis testing, sampling, survey analysis, forecasting, and model evaluation.
  • - Develop, test, validate, and document analytical models, forecasts, decision aids, and other advanced-analytics solutions when they provide meaningful business value.
  • - Assess assumptions, data quality, bias, uncertainty, and model limitations; communicate those considerations clearly to technical and nontechnical audiences, while identifying opportunities to automate recurring analysis and responsibly apply emerging analytics and AI capabilities.
Reporting, visualization, and self-service analytics
  • - Develop, enhance, and manage recurring, ad hoc, operational, compliance, and executive workforce reporting.
  • - Create intuitive dashboards and visualizations that make workforce trends, relationships, drivers, and implications easy to understand.
  • - Establish reporting standards, metric definitions, documentation, and reusable analytical assets to improve consistency and adoption.
  • - Enable stakeholders to access trusted workforce metrics and standard reports through self-service tools, providing guidance on appropriate use and interpretation.
  • - Communicate analytical findings through concise narratives, presentations, dashboards, and other decision-ready products.
Data, systems, and governance
  • - Serve as a subject-matter resource for workforce data, HR processes, HR information systems, reporting environments, and analytical tools.
  • - Manage or contribute to data-quality controls, reconciliation, testing, issue…
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