AI Business Analyst

As Senior Business Analysts, we play a key role in analyzing and redesigning processes, designing AI-ready workflows, and collaborating with technology and data teams to ensure solutions are operationally sound and aligned with business needs. We help teams adopt new agentic capabilities, build AI fluency, and integrate human-in-the-loop practices that support quality, compliance, and transparency. Over the next three years, we will support the scaling of agentic and digital technologies across Global Customer Operations, enabling improvements in efficiency, decision quality, and customer experience while helping the organization transition to a modern, intelligence-enabled operating model.
Job Description
The Senior Business Analyst supports the Director of Business Analysis and plays a key role in implementing agentic and AI-enabled capabilities across Global Operations. The successful candidate brings strong expertise in business analysis, process redesign, digital transformation, and change enablement, helping teams adopt intelligent workflows that improve efficiency, decision quality, and user experience.

As a Senior Business Analyst, you will:
· Improve operational efficiency and performance through AI-enabled and low-code solutions that enhance automation, analytics, and human decision-making. · Analyze and redesign workflows, applying process and value stream mapping to identify improvements and measurable outcomes.
· Collaborate with technology and data teams to structure workflows that support data-driven decision-making and enable effective automation.
· Support the introduction and adoption of autonomous agents and AI tools within defined operational boundaries, ensuring human oversight, transparency, and compliance.
· Define and track success metrics that demonstrate measurable improvements in speed, quality, and scalability across processes.
· Contribute to the development of an AI-ready culture, supporting stakeholder engagement, communication, and training as part of change management initiatives.
Key Responsibilities:
1. Business Analysis and Requirements Elicitation, translating business needs into actionable requirements that guide AI-enabled workflows and automation initiatives. Collaborate with stakeholders to ensure outcomes are measurable, aligned, and achievable.
2. Process Redesign and Value Stream Mapping, leading process mapping and improvement initiatives to identify inefficiencies, recommend automation opportunities, and design optimized agentic workflows.
3. Human-Agent Collaboration Design, defining workflows that enable collaboration between automation and human expertise, ensuring transparency, quality, and compliance.
4. Change Management and Stakeholder Alignment, enabling adoption of agentic and digital workflows through engagement, communication, and training across global teams.
5. Data-Driven Decision-Making, using analytics and metrics to validate assumptions, measure automation impact, and guide ongoing improvement.
6. Operating Model Awareness, supporting the design and implementation of AI-ready operating models that align process design with organizational goals.
7. AI Fluency, maintaining a working knowledge of agentic systems and AI technologies and applying them to rethink workflows, improve decisions, and drive intelligent automation.
8. AI-Enabled Analysis and Workflow Support, using AI tools to support analysis, summarization, documentation, ideation, and workflow design to improve accuracy, speed, and quality of deliverables.
9. AI Experimentation and Innovation, exploring new AI capabilities and features to identify opportunities for workflow innovation and continuous improvement.
10. Ethical AI and Governance Awareness, contributing to responsible AI adoption by following established governance frameworks and ensuring fairness, explainability, and compliance.
11. Reusable Pattern Design and Knowledge Sharing, identifying and sharing best practices and reusable workflow components to promote consistency and scalability across business units.
12. Collaboration and Delivery, building strong relationships with cross-functional partners in technology, data, and operations to deliver measurable transformation outcomes.
Desired Skills and Experience:
* Bachelor’s degree in a related field.
* Minimum of 5 to 7 years of experience in business analysis, process transformation, or digital operations, ideally within large-scale, AI-enabled environments.
* Experience or knowledge in legal, content, or operational domains, applying analysis skills in regulated or process-driven industries.
* Proven experience redesigning processes to enable agentic and AI-driven automation.
* Demonstrated success leading end-to-end process mapping and workflow improvement initiatives.
* Ability to reimagine workflows, challenge traditional approaches, and apply AI fluency to connect business needs with intelligent solutions.
* Experience working with AI or automation tools such as low-code platforms, RPA, process mining, or similar technologies.
* Strong analytical and quantitative skills with the ability to measure and communicate performance improvements.
· Strong communication and stakeholder management and relationship skills.
* Proven ability to work effectively across technical and business teams and translate complex ideas into clear, actionable insights.
* Experience supporting AI adoption and change management in cross-functional or global organizations.
* Awareness of responsible and ethical AI use, including fairness, transparency, and human oversight.
* Demonstrated ability to use AI tools in daily work, craft effective prompts, and treat AI as a collaborative partner in problem-solving and workflow design.
* Curiosity for emerging technology trends and willingness to explore AI capabilities through pilots, prototypes, and new ways of working.
* Demonstrated agile mindset with experience in iterative improvement and rapid learning.
Other considerations:
· Ability to travel as required (up to 10-20%), including domestic and international locations.

Technical & AI Elevation
AI-First Workflow Design
* Redesigns operating models assuming AI capability exists
* Understands agents, LLM limitations, and probabilistic outputs
* Intentionally designs human-in-the-loop guardrails
* Removes legacy constraints enabled by AI
Architectural & Integration Fluency
* Comfortable discussing APIs, system integrations, and data flows
* Engages credibly in solution design conversations with engineering
* Anticipates upstream/downstream technical impacts
AI Evaluation & Governance Awareness
* Defines quality thresholds and confidence models for AI features
* Understands evaluation concepts (precision, recall, drift, monitoring)
* Incorporates risk, auditability, and compliance into requirements
* Designs measurable pilot and experimentation frameworks
Data & Experimentation Orientation
* Frames initiatives as testable hypotheses
* Uses data to validate impact and iterate solutions
* Leads structured pilots for AI-enabled capabilities
Proactive Technology Orientation
* Actively evaluates emerging technologies
* Identifies opportunities to embed AI into enterprise workflows
* Demonstrates continuous learning in AI and platform evolution