AI-Native Outcomes & Value Analyst

Description
AI-Native Outcomes & Value Analyst
CONTINGENT UPON ANTICIPATED JANUARY 2027 WORK
This position is contingent upon the company securing the anticipated work in January 2027. Candidate consideration may occur before the decision; however, any offer, start date, and onboarding depend on the work being secured and authorized to proceed. January 2027 is the anticipated work decision period, not a guaranteed start date.
Position Summary
A client-facing senior analyst who measures whether AI-native transformation delivers the results organizations need. This role integrates rigorous data analysis with stakeholder consulting and practical understanding of generative AI to establish baselines, evaluate human-AI workflows, quantify realized benefits, and turn findings into decisions and continuous improvement. Success is defined by demonstrated business outcomes—not dashboard volume.
Requirements
Key Responsibilities
Lead client discovery sessions to translate strategic goals, operational challenges, and stakeholder questions into measurable outcomes, hypotheses, and analysis plans.
Design measurement frameworks for AI-enabled workflows, human-AI collaboration, agentic or automated processes, workforce adoption, quality, and operational effectiveness.
Establish reliable pre-implementation baselines, KPI definitions, target measures, comparison methods, and data-quality controls; document measurement assumptions and limitations.
Analyze data with SQL and business intelligence tools such as Power BI; create accessible visualizations and concise executive-ready narratives to explain trends and tradeoffs.
Apply generative AI and AI-assisted analytics appropriately, validating AI-produced summaries, calculations, classifications, and insights for accuracy, bias, privacy, and reproducibility.
Quantify productivity, cycle-time, quality, cost, capacity, and adoption improvements; support business cases, benefits tracking, ROI assessments, and attribution of realized value.
Partner with Agile delivery teams to embed iterative measurement in pilots, demonstrations, release reviews, feedback loops, and outcome-based improvement decisions.
Communicate actionable recommendations to executives, delivery teams, and operational stakeholders, including where expected value is not being realized and what to adjust.
Collaborate with data, product, operations, change management, and AI engineering teams to evaluate outcomes and sustain measurement after rollout.
Required Qualifications
Bachelor’s degree in Data Analytics, Statistics, Computer Science, Information Systems, Business Analytics, or a related field, or equivalent relevant experience.
7+ years of professional data analytics, business intelligence, performance measurement, or value realization experience, including stakeholder-facing analytical work.
Advanced SQL skills and experience with Power BI or comparable BI/data-visualization tools; ability to reconcile and validate data from multiple sources.
Demonstrated experience developing KPIs, baselines, benefit measures, and analyses that translate into operational recommendations and leadership decisions.
Practical experience using generative AI or AI-assisted analytics, with critical evaluation and verification of AI-generated outputs.
Experience delivering analytics in an Agile or iterative delivery environment and adjusting measurement approaches based on stakeholder feedback.
Strong analytical reasoning, communication, facilitation, executive presentation, and client collaboration skills.
Preferred Qualifications
Experience analyzing AI adoption, automated or agentic workflows, human-in-the-loop processes, or AI-enabled operating models.
Experience in a Scaled Agile Framework (SAFe) environment; SAFe Practice Consultant (SPC) certification preferred, not required.
Experience with ROI models, benefits realization, experiment design, statistical methods, and/or Python or R.
Experience supporting healthcare IT, federal government, or other regulated client environments.
Familiarity with responsible AI, data governance, privacy, and organizational change/adoption measures.
Measures of Success
Credible baselines and stakeholder-approved success measures exist for prioritized transformation initiatives.
Actionable findings influence delivery decisions, workflow redesign, adoption actions, or investment priorities.
Client leaders can see validated changes in productivity, cycle time, quality, adoption, efficiency, and realized business value.
Benefits are monitored after implement

Skills
Python, SQL, Data Analysis, Power BI, Generative AI, Agile, Onboarding

Experience
7+ yrs

Work arrangement
Yes