Senior HR Data Analytics Partner

Bronson Healthcare

2d•Onsite

About The Position

The Senior HR Data Analytics Partner serves as an enterprise‑wide analytical resource for Human Resources. Reporting to the Head of Total Rewards, this role supports all HR functions—including Benefits, Compensation, Retirement & Savings, HR Service Center, Talent Acquisition, Learning & Development, Employee Relations, HR Business Partners, and HRIS. This position transforms complex workforce data into accurate, meaningful, and actionable business intelligence. The analyst ensures the validity and reliability of HR data, interprets trends, identifies relationships, and develops fact‑based insights that help leaders understand what is happening, why it matters, and where action may be needed. Success requires strong analytical capability, business acumen, intellectual curiosity, exceptional collaboration, and disciplined follow‑through.

Requirements

Bachelor’s degree in Data Analytics, Business Analytics, Human Resources, Finance, Economics, Statistics, Business Administration, Healthcare Administration, Information Systems, or related field required
Minimum of five years of progressively responsible experience in data analytics, business intelligence, HR analytics, project management, Finance, Human Resources, healthcare analytics, or related field.
Demonstrated experience analyzing large and complex datasets, validating data, identifying data-quality issues, and translating findings into meaningful business insights.
Experience developing dashboards and visualizations using Power BI or comparable tools.
Experience coordinating complex, cross-functional projects.

Nice To Haves

Master’s degree preferred.
Experience working with senior leaders and developing executive-level presentations preferred.
Human Resources or healthcare experience strongly preferred.

Responsibilities

Collect, integrate, validate, analyze, and interpret data from multiple HR systems and functions.
Identify trends, relationships, risks, opportunities, and emerging workforce issues.
Connect recruitment, retention, compensation, benefits, engagement, turnover, learning, and workforce demographics to develop a comprehensive view of workforce performance.
Conduct trend, variance, comparative, and root‑cause analyses.
Develop meaningful HR metrics, KPIs, benchmarks, and comparative analyses using internal and external data.
Shift HR analytics from retrospective reporting toward predictive and forward‑looking workforce insights.
Perform ad hoc analyses in response to emerging workforce and business questions.
Convert complex datasets into concise, executive‑ready narratives.
Develop presentations that combine data, visualizations, key findings, and implications.
Identify the most important insights rather than simply presenting large volumes of data.
Provide context so leaders understand the significance of trends and variances.
Present alternative interpretations when data does not support a single conclusion.
Tailor analytical presentations for HR leaders, operational leaders, senior executives, and other audiences.
Use data storytelling to support informed decision‑making while avoiding unsupported conclusions.
Design, develop, and maintain Power BI dashboards and other analytical tools.
Create executive and operational dashboards that provide timely visibility into critical workforce measures.
Integrate information from multiple HR data sources into meaningful reporting.
Develop standardized reporting templates, scorecards, and automated recurring reports.
Improve access to HR information while maintaining appropriate data security.
Partner with HRIS and IT to enhance data integration and reporting capabilities.
Continuously evaluate opportunities to improve the efficiency, accuracy, and usefulness of HR reporting.
Ensure that HR data is accurate, credible, and appropriately interpreted.
Establish processes to validate data before analysis or executive reporting.
Reconcile information across HRIS, payroll, benefits, compensation, recruiting, learning, vendor, and financial systems.
Identify discrepancies, anomalies, missing information, and inconsistent definitions.
Partner with HRIS and HR functional leaders to resolve data‑quality issues.
Establish standardized definitions for key HR measures and metrics.
Document data sources, methodologies, assumptions, and limitations.
Develop repeatable quality‑control procedures for recurring HR reports and dashboards.
Distinguish clearly between facts, assumptions, correlations, and conclusions.
Communicate when available data is insufficient to support a definitive conclusion.
Maintain confidentiality and security of employee and workforce information.
Analyze medical, pharmacy, dental, and other benefit utilization and cost trends.
Evaluate employee and employer contributions, plan design modeling, affordability, and vendor performance.
Identify emerging benefit cost drivers and assess financial impact of proposed benefit changes.
Support market competitiveness analysis, salary structures, internal equity, pay compression, and compensation trends.
Conduct workforce cost modeling, benchmarking, and financial impact assessments for proposed compensation changes.
Provide analytical support for 403(b), 401(k), and other retirement programs.
Evaluate vendor performance, program changes, compliance‑related data, and plan modeling.
Analyze time‑to‑fill, time‑to‑start, vacancy rates, candidate pipelines, source effectiveness, recruiting costs, and offer acceptance.
Evaluate hard‑to‑fill positions, new‑hire turnover, and recruitment trends by job family, location, and department.
Support predictive analytics related to retirement, regrettable turnover, and long‑term vacancies.
Analyze inquiry volume, case types, response times, service‑level performance, repeat inquiries, escalations, and customer experience.
Identify opportunities for self‑service, automation, and process improvement.
Evaluate program participation, completion rates, mandatory training compliance, leadership development, onboarding, and learning utilization.
Assess program effectiveness and relationships between learning interventions and workforce outcomes.
Support analysis of headcount, FTE trends, turnover, retention, vacancy rates, workforce demographics, span of control, overtime, premium labor, contingent labor, absenteeism, engagement, productivity, succession, talent management, workforce planning, and labor costs.