Senior Analyst - Transformation - Consulting Product Analyst

General Position Information

Reports directly to (Title): Director or Senior Director, HR Transformation & Analytics

Matrix reports to (Title): -

Direct Reports: Individual contributor

Created / Last Revised: -

Job Code: -

Position Summary

The Senior Analyst - Transformation provides advanced, cross-functional advisory leadership for HR Transformation & Analytics. 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 Senior Analyst - Transformation supports HR Transformation & Analytics by measuring how HR products, tools, portals, workflows, automations, and analytics experiences are used and whether they deliver intended outcomes. This role partners with product owners, business analysts, BI developers, data analysts, change managers, and HR stakeholders to track adoption, usage, feature effectiveness, user friction, and value realization.

The role is responsible for product performance reporting, usage analysis, funnel analysis, experiment measurement, dashboard requirements, and product insight generation. Success requires product thinking, analytical discipline, stakeholder communication, and responsible use of AI-enabled product analytics tools.

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.

Product Usage & Adoption Analytics

• Track product adoption, active usage, feature utilization, completion rates, drop-offs, engagement patterns, and user segments.
• Analyze user journeys, friction points, workflow bottlenecks, and behavior patterns across HR digital products and analytics experiences.
• Develop product performance summaries that help teams understand what is working, what is not, and what should be improved.

Measurement, Experimentation & Value Tracking

• Support product KPI definitions, success measures, baselines, adoption targets, and post-release performance tracking.
• Analyze pilots, releases, experiments, enhancements, and process changes to determine impact and value delivered.
• Partner with product owners and analysts to translate findings into roadmap recommendations and prioritization inputs.

Dashboard, Data & Stakeholder Partnership

• Define analytics requirements for product dashboards, event tracking, data capture, and reporting views.
• Validate product data, document definitions, and identify gaps in telemetry, source systems, or user feedback.
• Communicate insights to product, transformation, operations, change, and leadership stakeholders in a clear and action-oriented manner.

AI-Augmented Product Analytics

• Use approved AI tools to support feedback clustering, insight drafting, product question framing, experiment summaries, and user behavior hypotheses.
• Validate AI-assisted findings against product data, user feedback, and business context before making recommendations.
• Identify opportunities to embed AI-assisted insight, self-service analytics, or intelligent product experiences into HR products.

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 feedback synthesis, insight generation, journey analysis, and recommendation drafting while validating against product evidence.
• Understands AI-enabled product analytics, privacy limits, and the need for transparent measurement definitions.
• Builds capability in augmented product analytics, experimentation, behavioral analytics, AI-assisted user research, and intelligent HR product measurement over the next three years.

Education & Experience

• Bachelor's degree in Business, Human Resources, Information Systems, Computer Science, Data Analytics, Statistics, Engineering, 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 with product analytics, business analytics, reporting, user behavior analysis, process analytics, HR technology, or digital product support.
• Experience analyzing adoption, usage, workflow, operational, or customer/user experience data.
• Experience creating product performance reports, dashboards, summaries, or recommendations for product or business stakeholders.

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 skills and ability to interpret product usage, adoption, funnel, and performance metrics.
• Working knowledge of Excel, SQL, BI tools, product analytics tools, or data visualization platforms.
• Ability to define product metrics, document assumptions, validate data, and explain limitations.
• Product mindset with the ability to connect user behavior to experience, process, and business outcomes.
• Strong communication skills for translating analysis into actionable product recommendations.
• Ability to partner with product owners, business analysts, change managers, and technical teams.
• Foundational AI literacy for product insight generation, feedback analysis, narrative drafting, 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 systems, employee experience platforms, service portals, workflow tools, analytics products, or automation products.
• Exposure to product analytics tools such as Pendo, Amplitude, Mixpanel, Google Analytics, Adobe Analytics, or in-product telemetry.
• Experience with experimentation, A/B testing, release measurement, user research, or voice-of-customer analysis.
• Experience with Power BI, Tableau, SQL, Python, R, or statistical analysis tools.
• Prior experience in healthcare, shared services, HR operations, or regulated environments.
• Exposure to Agile product delivery, Jira, Confluence, product roadmaps, or backlog prioritization.
• Experience using AI to summarize feedback, generate hypotheses, or support product analytics workflows.

Licenses, Certifications & Training

• 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.