Senior Analyst - Data Science

Consulting Business Insights Analyst - Formatted Job Posting

General Position Information

Reports directly to (Title): Manager, Advanced Analytics and Data Science

Matrix reports to (Title): As applicable based on HR Transformation & Analytics portfolio, platform, product, or functional alignment

Direct Reports: Individual contributor; may provide advisory direction, standards, and workstream guidance

Created / Last Revised: 07/02/2026

Job Code: TBD

Position Summary

The Consulting Business Insights Analyst provides advanced, cross-functional advisory leadership for the Human Resources Group (HRG). This role is used for complex, ambiguous, or enterprise-impacting work that requires deep functional expertise, strong stakeholder influence, standards-setting, and the ability to connect business outcomes, data, technology, process, product, and AI-readiness considerations across multiple teams or portfolios.

The Business Insights Analyst supports HRG by turning HR, workforce, operational, product, and transformation data into clear insights, narratives, and recommended actions. This role partners with HR leaders, analytics teams, business stakeholders, product owners, process teams, and reporting partners to interpret trends, identify risks and opportunities, and prepare insight materials for business reviews and decision-making.

The role bridges analytics and business context. It is responsible for asking the right questions, validating data interpretations, developing executive-ready insight summaries, and helping stakeholders understand what is happening, why it matters, and what actions should be considered.

Responsibilities

Consulting-Level Advisory & Cross-Functional Leadership

• Serve as a trusted advisor on complex HR Transformation & Analytics initiatives that span multiple stakeholders, systems, functions, or business outcomes.
• Shape solution direction, operating approach, delivery standards, analytical methods, technical patterns, or governance practices for assigned areas of expertise.
• Lead complex discovery, problem framing, impact analysis, stakeholder alignment, and recommendation development where ownership or solution paths are not yet clear.
• Influence leaders and cross-functional partners through structured analysis, executive-ready communication, trade-off framing, and practical implementation recommendations.
• Establish reusable practices, playbooks, quality standards, templates, and decision frameworks that improve consistency and maturity across the HR Transformation & Analytics organization.

Insight Development & Business Interpretation

• Analyze workforce, HR operations, transformation, product, and service data to identify patterns, root causes, risks, opportunities, and recommended actions.
• Develop insight narratives, business review materials, and executive summaries that translate data into practical decisions.
• Connect quantitative findings with qualitative inputs such as stakeholder feedback, operational context, process changes, and adoption signals.

Performance Monitoring & Decision Support

• Support recurring business reviews, leadership updates, metric reviews, and portfolio performance discussions.
• Track performance against goals, baselines, service levels, adoption targets, and transformation outcomes.
• Highlight material changes, emerging trends, and data limitations that require leadership attention or deeper analysis.

Stakeholder Partnership & Framing

• Work with business stakeholders to clarify the decision being supported, define the business question, and determine the most relevant metrics or evidence.
• Partner with reporting analysts, BI developers, data analysts, product analysts, and data owners to validate definitions, sources, and analysis outputs.
• Prepare presentations, briefing materials, storylines, and follow-up analysis for cross-functional audiences.

AI-Enabled Insight Generation

• Use approved AI tools to support hypothesis generation, pattern exploration, meeting synthesis, draft narratives, and alternative ways to explain findings.
• Validate AI-assisted summaries, avoid unsupported conclusions, and ensure recommendations are grounded in approved data and business context.
• Identify opportunities to improve insight speed, consistency, and accessibility through AI-assisted analytics workflows.

AI Preparedness Expectations

• Shapes responsible AI adoption patterns for assigned domains, including appropriate use cases, controls, human review expectations, validation approaches, and stakeholder readiness.
• Advises leaders and cross-functional partners on how AI can improve productivity, insight generation, engineering, analytics delivery, process maturity, product outcomes, and workforce readiness.
• Establishes or contributes to reusable AI guidance, prompt patterns, quality checks, governance artifacts, and adoption practices that reduce risk and improve consistency.
• Builds advanced capability in AI-enabled operating models, responsible AI governance, AI-assisted analytics and engineering, and future-of-work implications over the next three years.
• Uses AI to accelerate synthesis, hypothesis generation, narrative drafting, and stakeholder-ready summaries without substituting AI output for judgment.
• Can evaluate whether AI-assisted conclusions are supported by source data, business context, and approved metric definitions.
• Builds capability in AI-assisted data storytelling, augmented analytics, responsible AI interpretation, and decision intelligence

Education & Experience

• Bachelor's degree in Computer Science, Data Analytics, Statistics, Engineering, Economics, or a related field; equivalent experience may be considered.
• Typically 5+ years of experience in a related environment.
• Experience leading complex cross-functional initiatives, advisory engagements, enterprise analytics, technology delivery, transformation workstreams, or process improvement efforts.
• Experience influencing leaders, resolving ambiguity, framing decisions, and presenting recommendations to senior managers, directors, or senior directors.
• Experience establishing standards, governance practices, reusable frameworks, playbooks, or capability maturity improvements across teams or portfolios.
• Experience analyzing business, HR, workforce, operations, product, or transformation data and preparing insights for stakeholders.
• Experience creating summaries, presentations, scorecards, or business review materials that explain performance trends and actions.
• Experience working with cross-functional stakeholders to clarify business questions and translate analysis into recommendations.

Must Have Skills

• Advanced advisory capability with the ability to frame ambiguous problems, assess trade-offs, and recommend practical enterprise or cross-functional solutions.
• Strong executive communication skills, including the ability to convert complex analysis, process, technology, product, or data issues into clear decisions and actions.
• Demonstrated ability to establish standards, governance practices, methods, templates, or playbooks that improve consistency and maturity across teams.
• Ability to influence senior stakeholders and cross-functional partners while balancing business outcomes, risk, feasibility, scalability, and user impact.
• Strong analytical and critical-thinking skills, including the ability to move from data observations to business implications.
• Ability to synthesize complex information into clear storylines, executive summaries, and recommended actions.
• Working knowledge of Excel, PowerPoint, and at least one reporting, dashboarding, or analytics tool.
• Comfort interpreting HR, workforce, operational, product, or transformation metrics and explaining data limitations.
• Strong written and verbal communication skills for both analytical and non-technical audiences.
• Ability to manage recurring deliverables and ad hoc requests with strong attention to detail.
• Foundational AI literacy for insight drafting, summarization, pattern exploration, and quality checks using approved tools.

Nice To Have Skills

• Experience advising executive or senior leadership audiences on complex workforce, HR, analytics, product, technology, process, or transformation decisions.
• Experience developing capability models, roadmaps, governance frameworks, maturity assessments, standards, or enterprise playbooks.
• Experience shaping responsible AI adoption, data governance, analytics modernization, automation strategy, or AI-enabled workforce readiness practices.
• Experience with HR analytics, workforce planning, talent analytics, employee listening, HR operations, shared services, or transformation reporting.
• Exposure to Power BI, Tableau, SQL, Python, R, or statistical analysis tools.
• Experience supporting executive business reviews, leadership scorecards, OKRs, or transformation value tracking.
• Prior experience in healthcare, shared services, global capability centers, or regulated environments.
• Knowledge of change adoption, product adoption, operational excellence, or process improvement metrics.
• Exposure to storytelling with data, visual communication, design thinking, or consulting-style presentation development.
• Experience using AI tools for meeting synthesis, insight brainstorming, narrative development, or research support.

Licenses, Certifications & Training

• N/A required.
• Preferred: role-relevant certification, analytics platform training, data governance training, or Agile delivery training, as applicable.
• Preferred: Responsible AI, data privacy, data security, or HR data handling training.

Knowledge, Skills, Abilities, Behaviors

• Demonstrates curiosity, ownership, and sound judgment when working with HR data, systems, processes, and stakeholders.
• Communicates status, assumptions, risks, and limitations clearly without overstating what the data, process, or technology can support.
• Works collaboratively across HR, technology, analytics, product, operations, and transformation partners in a matrixed environment.
• Protects confidential HR and workforce information and follows internal privacy, security, data governance, and compliance expectations.
• Uses AI tools with professional skepticism, validates AI-assisted outputs, avoids entering restricted data into unapproved tools, and escalates AI or data risks appropriately.
• Maintains documentation discipline, change awareness, customer focus, and continuous improvement mindset while balancing multiple priorities.