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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Assistant Manager - Data and AI Transformation - Tech Consulting - EY Mauritius - **Company:** Ernst & Young GmbH - **Location:** Stuttgart, Germany - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, JIRA, Microsoft Azure, Business Process Model and Notation, Information Systems, Information Extraction, Machine Learning, Microsoft Visio, Scrum Methodology, Lucidchart, Microsoft Copilot, Robotic Automation Software, Service Design, Chatbots, Signavio, Aris Software, Generative AI, AI Platforms, Information Technology, Virtual Agents - **Published:** November 11, 2026 - **Apply:** https://careers.ey.com/talentcommunity/apply/1456290733/?locale=en_GB ## About the Role The Assistant Manager will help clients reimagine and improve business processes and operations by combining strong business analysis and process transformation skills with practical knowledge of data and artificial intelligence, including generative AI, machine learning, intelligent automation and emerging agentic capabilities. The role will translate business priorities and operational pain points into clear current-state insights, future-state processes and designs, requirements, value cases and implementation roadmaps. The successful candidate does not need to be a data scientist or AI engineer. They must, however, be able to work confidently at the intersection of business, process, people, data and technology, and be motivated to build deeper expertise in AI-enabled transformation with a solid foundation of digital project experience., * A relevant degree in business, information systems, industrial engineering, operations management, technology management or a related discipline. * Typically 5 years of relevant experience in business analysis, process improvement, digital transformation, digital and or data projects, consulting, operational excellence, product delivery or a related field. Equivalent capability and progression will be considered. * Demonstrated experience analysing and redesigning end-to-end business processes, not only documenting them. * Experience gathering and structuring requirements and translating between business and technical stakeholders. * Experience facilitating client or internal workshops and presenting findings and recommendations to senior stakeholders. * Experience managing defined workstreams, priorities, risks and junior contributors. * Strong written and verbal English. French capability is advantageous for the Mauritius and regional market. (ii) Core skills and behaviours Capability What good looks like Process analysis and design Current-state and future-state mapping, root-cause analysis, business rules, controls, hand-offs, exceptions, customer journeys and process performance. Business analysis Requirements elicitation, stakeholder analysis, user stories, acceptance criteria, traceability and structured documentation. Commercial and value orientation Ability to connect redesign choices to efficiency, experience, risk, revenue, service quality and measurable outcomes. AI and data literacy Practical understanding of AI concepts, data dependencies, data modelling, AI model prompting and outputs, limitations and appropriate human oversight. Deep model-building expertise is not required. Consulting communication Workshop facilitation, executive storytelling, concise writing, visual communication and constructive challenge. Delivery discipline Planning, prioritisation, issue resolution, quality review and ownership of outcomes. Learning agility Curiosity, experimentation and commitment to continuous learning in a rapidly evolving AI landscape. Responsible transformation Awareness of privacy, security, bias, explainability, control, regulatory and change implications., * Consulting experience with exposure to financial services, public sector, healthcare, telecommunications, consumer, energy or other process-intensive industries. * Exposure to ERP, CRM, workflow, intelligent automation, RPA, process mining, service design, operating model or shared services programmes. * Hands-on use of tools such as Microsoft Copilot, Power Platform, Signavio, ARIS, Bizagi, Visio, Lucidchart, Jira, Azure DevOps or equivalent. * Understanding of BPMN, Lean, Six Sigma, Agile, product management or change management methods. * Experience assessing or implementing generative AI, machine learning, document intelligence, conversational AI, decision-support or AI agent use cases. * Experience with data modelling and EDM * Project management and or workstream management experience * Relevant certifications such as CBAP/CCBA, Lean Six Sigma, BPMN, Prosci, Scrum/Product Owner, Microsoft AI-900 or Power Platform fundamentals., AI depth will be assessed through interview process as a combination of baseline literacy, practical curiosity, sound judgement and learning potential. ## Description * Lead or support stakeholder interviews, workshops and working sessions to understand strategic objectives, customer and employee needs, pain points, controls and operational constraints. * Document current-state processes, business rules, roles, hand-offs, systems, data inputs/ requirements, decisions, exceptions and performance measures. * Translate business needs into well-structured business, functional, data, reporting, workflow and control requirements. * Maintain traceability from business objectives and pain points through requirements, design decisions and expected outcomes., * Identify process activities that could be eliminated, simplified, standardised, automated or augmented using AI and digital technologies. * Design future-state processes that combine human judgement with generative AI, machine learning, intelligent automation and workflow capabilities. * Define appropriate human-in-the-loop controls, escalation paths and accountability for AI-supported decisions and outputs. * Assess implications for roles, skills, decision rights, governance, data, technology, controls and ways of working. * Develop process blueprints, service journeys, operating model components and practical transition roadmaps. 3. Use case assessment and value realisation * Frame and prioritise AI and automation use cases based on strategic alignment, business value, feasibility, data readiness, risk and adoption considerations. * Develop value hypotheses, baseline measures, KPIs and benefit tracking approaches. * Support business cases, options analysis, recommendations, implementation plans and executive decision materials. * Help clients move from isolated ideas or proofs of concept toward scalable, governed and measurable solutions. 4. Delivery and implementation support * Work with data architects, data scientists, engineers, automation specialists, designers, change professionals and client teams to convert business designs into implementable solutions. * Support prototyping, user story development, acceptance criteria, testing, process validation and implementation readiness. * Monitor delivery risks, dependencies, actions and decisions, escalating issues where required. * Support adoption through stakeholder engagement, communications, training inputs, playbooks and updated process documentation. 5. Consulting and team contribution * Manage defined workstreams and junior team members, ensuring high-quality and timely outputs. * Prepare clear, concise and executive-ready presentations, reports and proposals. * Contribute to proposals, credentials, thought leadership, reusable methods and market-facing offerings. * Share knowledge and coach colleagues on business analysis, process redesign and practical AI application. * Build trusted relationships with client stakeholders and collaborate effectively across EY teams and geographies. * Other cognate duties, Explain AI, machine learning and generative AI in business terms Apply AI use-case and process redesign methods consistently Build or tune production machine-learning models Recognise that AI depends on data, controls and adoption Use approved AI tools to accelerate analysis and deliverables Act as the solution architect or lead engineer Identify plausible augmentation and automation opportunities Assess value, feasibility, risk and human oversight Be an expert in every AI platform Discuss limitations and validate AI outputs Contribute to prototypes and implementation requirements Replace specialist data science, architecture or engineering roles Success measures for the first 12 months: * Independently leads process discovery and future-state design for a defined client workstream. * Produces high-quality, traceable process, requirements and executive deliverables with limited rework. * Identifies and shapes credible AI-enabled transformation opportunities with clear value, feasibility, risk and adoption considerations. * Builds trusted relationships with client and EY stakeholders and contributes positively to team development. * Completes an agreed AI learning pathway and demonstrates practical application on engagements and internal assets. * Contributes to at least one reusable methodology, proposal asset, case study or market-facing point of view.