Senior Business Analyst - Pricing, AI & Data Readiness

Senior Business Analyst role in an international transformation program for a large organization in the energy sector. The role focuses on Pricing, AI, and Data & Analytics and involves working on AI initiatives in pricing processes and preparing data, processes, and the organization for scaled implementation of new solutions.

• Experience as senior Business Analyst.
• Experience in large business and technology transformations.
• Knowledge of Data & Analytics.
• Experience handling requirements and processes.
• Experience with UAT and implementations.
• Experience working with global stakeholders.

Nice to have:

• Experience in Pricing.
• Experience with AI / GenAI / Machine Learning initiatives from a business perspective.
• Experience in defining AI use cases.
• Knowledge of Data Quality / Data Readiness.
• Experience with BI and analytics.
• Knowledge of Responsible AI or governance.
• Experience in projects across multiple countries or business units.
• Understanding of data-driven solution workflows and ability to connect business, domain experts, and technical teams effectively.

Discovery and Business Analysis:

• Conduct workshops with Pricing, Finance, business, data teams, and technical stakeholders.
• Identify business problems and improvement opportunities.
• Define personas, AS-IS/TO-BE processes, pain points, and expected results.
• Translate needs into business and functional requirements.
• Create epics, user stories, business rules, and acceptance criteria.
• Build process maps and user journeys.
• Maintain traceability between business needs, requirements, tests, and solution adoption.

AI use cases in Pricing:

• Define and prioritize AI use cases.
• Determine business decisions supported by solutions.
• Define user interactions with solutions.
• Establish human-in-the-loop models.
• Define expected results and success metrics.
• Specify explainability needs.
• Collaborate on data and ground truth for solution evaluation.
• Coordinate user feedback and pilot evaluation.
• Recommend scaling, changes, or closure of use cases.
• Address business aspects of Responsible AI, data protection, security, and required approvals.

Data readiness:

• Support backlog and roadmap of data & analytics products.
• Coordinate readiness of countries and business units.
• Support data validation and quality issue resolution.
• Analyze issues with source systems, mapping, pricing logic, dashboards, and downstream consumption.
• Improve business rules and validation scenarios.
• Maintain visibility of open data-quality issues, decisions, and corrective actions.
• Prepare user materials, communication, and documentation for global and local teams.

UAT, rollout, and adoption:

• Prepare UAT strategy and scenarios.
• Coordinate tests and retests.
• Conduct defect triage.
• Recommend business sign-off.
• Assess release readiness.
• Manage communication and training.
• Measure adoption and business outcomes.