Analyst I - Transformation

General Position Information

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

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

Direct Reports: Individual Contributor.

Created / Last Revised: -

Job Code: -

Position Summary

The Analyst I – Transformations leads higher-complexity work within HR Transformation & Analytics, owning major deliverables, improving delivery quality, and translating business, data, technology, product, or process needs into reliable outcomes. This role operates with greater independence than the unprefixed level and is expected to lead workstreams, resolve ambiguity, mentor peers, and manage stakeholder expectations across HR, analytics, technology, operations, and transformation partners.

The Product Analyst 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

Senior-Level Ownership & Delivery Leadership

• Lead complex deliverables, workstreams, analyses, designs, builds, or implementation activities with limited oversight.
• Translate ambiguous stakeholder needs into clear scope, success measures, requirements, plans, technical outputs, or recommendations.
• Review deliverables for accuracy, usability, governance alignment, stakeholder readiness, and business value before release or handoff.
• Mentor less experienced team members by sharing standards, reviewing work, and reinforcing documentation, testing, and delivery discipline.
• Identify delivery risks, data or process limitations, technical dependencies, and stakeholder alignment issues early and recommend practical mitigation actions.

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

• Applies approved AI tools to accelerate complex deliverables, documentation, quality review, analysis, code, design, workflow support, or stakeholder materials while validating outputs before use.
• Identifies appropriate AI augmentation opportunities within assigned workstreams and helps teammates adopt safe, practical, and repeatable AI-enabled practices.
• Reviews AI-assisted outputs for accuracy, bias, completeness, privacy risk, governance alignment, and business context before release or recommendation.
• Builds deeper capability in AI-enabled HR analytics, workflow automation, decision support, and human-in-the-loop review 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 3+ years of experience in a related environment.
• Experience leading a defined workstream, analysis, product, technical deliverable, process improvement, reporting solution, or change initiative with cross-functional stakeholders.
• Experience reviewing deliverables, validating outputs, managing dependencies, and communicating risks or recommendations to managers, senior managers, or directors.
• Experience mentoring others, improving team standards, or contributing to repeatable methods, documentation, templates, or quality practices.
• 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

• Ability to independently lead complex workstreams or deliverables from intake through execution, validation, and stakeholder communication.
• Strong stakeholder management skills, including the ability to clarify expectations, manage dependencies, communicate risks, and influence decisions without direct authority.
• Demonstrated ability to review work for quality, accuracy, business relevance, data sensitivity, and operational readiness.
• Ability to mentor peers or junior team members and reinforce standards, documentation practices, and repeatable delivery methods.
• 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 serving as a subject matter expert, workstream lead, or delivery lead in HR, analytics, technology, transformation, shared services, or a regulated environment.
• Experience creating reusable templates, standards, training materials, quality checklists, or enablement content for team use.
• Experience applying approved AI tools to improve productivity, documentation quality, analysis, engineering, design, or stakeholder communication.
• 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.