Entry-Level Data Analyst, Workforce Analytics

About the role

This Entry-Level Data Analyst, Workforce Analytics role is structured around learning and contribution in equal measure. You will be assigned to a Senior Analyst in the People Science practice who will oversee your development and integrate you into active client workstreams on compensation survey data collection and management. We track progress formally and provide feedback regularly. We believe that is the only honest way to develop talent.

This is a role for an Entry-Level Data Analyst, Workforce Analytics who wants to understand how compensation really works — not as an abstraction but as data, methodology, and client application. You will support the People Science team in compensation survey data collection and management, contributing to deliverables that our analysts and managers take into client meetings. Your name will appear on the work. That matters to us.

ACPWB is looking for an Entry-Level Data Analyst, Workforce Analytics with a genuine interest in compensation survey data collection and management and the discipline to develop professional-grade analytical skills. If you are the kind of person who read the job description and wanted to know more, you are probably the kind of person we are looking for.

The ACPWB Analyst Development Program will give you structure. Your Senior Analyst will give you context. The rest is up to you.

Responsibilities

• Assist in maintaining and updating ACPWB's proprietary benchmarking data libraries
• Enter and verify data in ACPWB's compensation benchmarking databases under the supervision of a Senior Analyst
• Provide research support for ACPWB thought leadership publications and white papers on compensation survey data collection and management
• Conduct literature reviews and desktop research on topics relevant to compensation survey data collection and management
• Assist with survey administration including data collection follow-up and respondent tracking

Qualifications

• Demonstrated intellectual curiosity and a habit of asking questions when something is unclear
• GPA of 3.3 or above, or equivalent demonstrated academic performance
• Demonstrated ability to manage time, prioritize competing tasks, and meet deadlines without constant supervision
• Comfortable working with large spreadsheets and structured data

Preferred

• Familiarity with any benchmarking or survey platform (Radford, Mercer, WTW, or similar)
• Experience supporting a professional team in a coordinator or assistant capacity
• Demonstrated interest in workforce equity, pay transparency, or labor market policy
• Multilingual capability, particularly Spanish, for support on multinational client research

Why ACPWB

ACPWB occupies a distinctive position: large enough to be credible, small enough to be agile, old enough to have a track record, young enough to still be building it. The people who thrive here find that combination energizing rather than disorienting. ACPWB was founded in Milwaukee in 2006 with a simple mandate: help working Americans understand and advocate for the compensation they deserve. Eighteen years later, that mandate has grown into a full-service research and advisory practice serving clients from early-stage employers to Fortune 50 enterprises — and we are still based in Milwaukee, because Milwaukee is genuinely underrated.

Interview Process

We use a structured, competency-based interview format with a standardized scoring rubric applied consistently across all candidates. This approach is less exciting than an unstructured conversation but more predictive and considerably fairer. Interviewers are trained on the rubric before they use it.

What Success Looks Like In Year One

• Ask good questions consistently — about methodology, about client context, about why we do things the way we do
• Receive a mid-year performance review that confirms you are progressing on the expected development path
• Complete your first annual performance review cycle with documented goals for year two
• Demonstrate consistent accuracy in data entry and analysis work with a declining error rate over time