Entry-Level Data Analyst, Workforce Analytics

About the role

The Entry-Level Data Analyst, Workforce Analytics is an entry point into ACPWB's Human Capital Advisory practice for candidates who are serious about building a career in compensation data research and analysis. You will work alongside experienced advisors and analysts, contributing to real deliverables from your first week. This role is structured around learning and contribution in equal measure. You will be assigned to a Practice Lead in the Human Capital Advisory practice who will oversee your development and integrate you into active client workstreams on compensation data research and analysis. We track progress formally and provide feedback regularly.

Responsibilities

• Assist with survey administration including data collection follow-up and respondent tracking
• Participate in training modules as part of the ACPWB Analyst Development Program and complete assigned coursework on schedule
• Support the Human Capital Advisory team's engagement logistics including file management and documentation
• Maintain and update ACPWB's proprietary benchmarking data libraries
• Shadow client meetings and preparation sessions to build understanding of client-facing advisory work
• Contribute to the development of standard templates and analytical tools used by the Human Capital Advisory team

Qualifications

• Strong research skills including ability to find and synthesize information from multiple sources
• Demonstrated ability to manage time, prioritize competing tasks, and meet deadlines without constant supervision
• Comfort working in a structured environment with defined standards and quality expectations
• Strong written and verbal communication skills with attention to detail and grammatical precision
• Demonstrated proficiency in Microsoft Excel including pivot tables, VLOOKUP, and basic charting

Preferred

• Familiarity with any benchmarking or survey platform (Radford, Mercer, WTW, or similar)
• Demonstrated commitment to professional development, including self-directed learning
• Prior internship in HR, finance, consulting, or data analysis
• Demonstrated ability to produce clean, professional-quality work products

What Success Looks Like In Year One

• Take ownership of at least one recurring team responsibility — a data update, a tracking log, a template — and execute it reliably
• Identify one area where you can add unique value to the team — and begin doing so
• Contribute independently to at least two full engagement cycles, from data collection through final review
• Ask good questions consistently — about methodology, about client context, about why we do things the way we do
• Demonstrate consistent accuracy in data entry and analysis work with a declining error rate over time