Business Analyst, AI

So, what’s the role all about?

NiCE is building SPARK, a new internal incubation team that turns great ideas from across CX International into working AI solutions, and then into enterprise-grade tools that roll out to colleagues around the world. Your idea. Our spark.

As Business Analyst in the SPARK team, you will be the bridge between the people who have the ideas and the architects and builders who make them real. You will shape raw ideas into clear, prioritised, buildable use cases, and make sure what we build solves the problem it was meant to solve.

This is a business analysis role with a technical edge. You come from a programming background, so you can read code, query data, test an API, and prototype a quick proof of concept, and you can still run a room full of non-technical stakeholders. You will work closely with the Project Manager, the AI Architects & Builders, and the Change Management & Evangelist.

How will you make an impact?

You will own the front end of the incubation pipeline, from the first conversation about an idea through to accepted, measurable outcomes, working hands-on with business teams, architects, and delivery colleagues across regions.

Discover and Shape Ideas

• Run discovery sessions, interviews, and workshops with business teams to understand pain points, current processes, and the outcome they want
• Turn ideas into clear use case briefs covering the problem statement, users, expected value, data needs, risks, and success measures
• Assess and rank ideas against business value, feasibility, data readiness, effort, and risk, and give the team a clear recommendation on what to build next
• Build lightweight business cases, including estimated time saved, quality gains, and cost or revenue impact for presentation to Management and AI steering committee

Define What Gets Built

• Map as-is and to-be processes, and identify where an AI agent, an automation, or a human-in-the-loop step fits best
• Write user stories, acceptance criteria, and edge cases that architects and builders can build from without guesswork
• Specify expected AI behaviour: what the solution should do, what it should never do, when it hands over to a person, and how answers will be checked for quality
• Prepare test scenarios and evaluation datasets with the builders to measure accuracy, reliability, and usefulness before launch
• Update initiative register

Prototype and Validate

• Use SQL, Python, or low-code tools to analyse process data, test assumptions, and build simple prototypes that prove an idea before engineering effort is committed
• Review APIs and system documentation to confirm integration feasibility with enterprise platforms such as Salesforce, ServiceNow, Workday, and Microsoft 365
• Gather early user feedback on prototypes and turn it into prioritised backlog items

Support Delivery and Adoption

• Own and groom the product backlog, and take part in sprint planning, reviews, and retrospectives
• Plan and run user acceptance testing with business users, and manage defects and feedback through to closure
• Partner with the Change Management & Evangelist and the Support Helpdesk to turn user questions and feedback into clear improvements

Measure and Share Value

• Capture baseline metrics before launch and track results afterwards, so every solution can show real impact
• Understand the