AI Business Performance & Insights, Senior Analyst

KeyBank•Brooklyn, OH

1d•$71,000 - $125,000•Hybrid

About The Position

The Performance & Insights Senior Analyst is responsible for measuring business performance and surfacing actionable quantitative and qualitative insights that inform leadership decisions, improve effectiveness, and drive better outcomes. This role goes beyond reporting—connecting performance data, employee sentiment, and feedback loops to assess progress against expectations and identify opportunities to improve impact, adoption, and results. This individual serves as a thought partner to leaders, translating data into insight, insight into action, and action into measurable improvement. The role also plays a critical enablement function—reinforcing data standards and practices that ensure insights are scalable, governed, and ready to support automation and AI‑driven capabilities.

Requirements

5 years of experience in business performance measurement, analytics, or insights-driven roles
Demonstrated ability to combine quantitative data with qualitative insight to inform decisions
Experience designing and interpreting KPIs, scorecards, and performance frameworks
Proven skill in translating data into clear, compelling insights for senior leaders
Experience using data visualization and analytics tools (e.g., dashboards, survey platforms, BI tools)
Insight-driven: Sees beyond metrics to understand root causes and implications
Outcome-oriented: Focused on impact, effectiveness, and value—not just measurement
Analytical & human‑centered: Balances data rigor with employee experience and context
Executive communicator: Distills complexity into clear, decision‑ready insights
Enablement‑minded: Encourages standards and reuse without becoming a control function
Continuous improver: Constantly looking for better ways to measure, learn, and drive results
Comfort working in ambiguity and influencing without authority
Data Analysis & Insight Generation: Demonstrated ability to combine quantitative data with qualitative insight to inform decisions
KPI & Performance Framework Design: Experience designing and interpreting KPIs, scorecards, and performance frameworks
Executive Insight Storytelling: Proven skill in translating data into clear, compelling insights for senior leaders
Insight‑Driven Thinking: Sees beyond metrics to understand root causes and implications
Outcome Orientation: Focused on impact, effectiveness, and value—not just measurement
Analytical & Human‑Centered Approach: Balances data rigor with employee experience and context
Executive Communication: Distills complexity into clear, decision‑ready insights
Enablement Mindset: Encourages standards and reuse without becoming a control function
Continuous Improvement: Constantly looking for better ways to measure, learn, and drive results
Ambiguity Navigation & Influence: Comfortable working in ambiguity and influencing without authority
Data Visualization & Analytics Tools: Experience using dashboards, survey platforms, and BI tools

Nice To Haves

Background in digital, product, operations, or strategy environments
Experience with employee engagement, sentiment analysis, or organizational effectiveness
Experience with change management, adoption measurement, or transformation initiatives

Responsibilities

Define, govern and maintain performance frameworks that measure progress against strategic goals, commitments, and expected outcomes, ensuring consistency, comparability and credibility across business areas
Establish and manage KPIs, success metrics, and scorecards that reflect outcomes and effectiveness—not just activity
Assess performance trends, gaps, and risks, clearly articulating what is working, what is not, and why
Synthesize quantitative data (metrics, dashboards, operational performance) with qualitative inputs (employee feedback, sentiment, observations) to deliver holistic insights
Identify leading and lagging indicators that predict performance outcomes and business impact
Translate complex data into clear, executive‑ready narratives that inform decision making
Design and manage feedback mechanisms (surveys, pulse checks, listening posts, qualitative interviews) to capture employee sentiment and experience
Analyze themes, patterns, and sentiment trends to understand engagement, friction points, and change readiness
Partner with leaders to close feedback loops—ensuring insights result in visible action and measurable improvement
Evaluate the effectiveness of initiatives, operating models, and ways of working against intended outcomes
Identify opportunities to improve performance, adoption, efficiency, and value realization
Support experimentation and continuous improvement by defining success criteria and measuring impact over time
Serve as a connector between AI enablement, analytics, data governance, and business teams to ensure AI insights are scalable, governed, and reusable
Support the transition from AI experimentation to production‑ready, business‑aligned capabilities by reinforcing standards, expectations, and performance implications
Encourage use of governed, standardized data assets to support AI models and automation—highlighting where unmanaged data limits scale or increases risk
Influence data and insight standards to ensure performance intelligence is production-ready, auditable and fit for AI-driven decision support.
Use performance and adoption insights to surface AI‑related governance gaps, duplication, or unmanaged experimentation that create risk or inefficiency
Act as a trusted advisor to business and functional leaders, providing objective insight and data‑driven recommendations
Influence prioritization and decision making by grounding discussions in evidence, outcomes, and trade‑offs
Collaborate across teams (analytics, operations, change, communications) to align insights, performance narratives, and adoption strategies