One of our clients is seeking a Business Analyst with a strong focus on AI
Full time permanent position
Hybrid / Berlin
Fluent German
You MUST have AI experience.
You bridge the gap between business operations and AI possibility — mapping how work actually flows today, and showing what it could realistically look like tomorrow. This is a role for someone equally at home in a stakeholder workshop, a BPMN diagram, and a cost model.
You start every project by understanding the problem deeply — the people, the data, the friction, the systems of record. Then you figure out where AI can genuinely help, where an existing PropTech vendor already does it better, and what it would actually cost and save to get there. You are the person who keeps us from automating a broken process or building something we should have bought.
What you'll do:
1. Run structured stakeholder interviews across asset management, property management, leasing, finance/controlling, and ESG to surface the processes where AI could create real value. Document current-state and target-state processes using BPMN, Visio, or comparable notation — at a level of rigour that engineers, vendors, and auditors can all work from.
2. Build the business case for each opportunity: cost-to-serve today, expected savings, implementation cost, payback, and the assumptions behind every number.
3. Apply build-vs-buy discipline as a default mindset. Before greenlighting any internal build, evaluate whether a PropTech or horizontal SaaS vendor already solves the problem better, faster, or cheaper — and document the reasoning either way.
4. Map every initiative to the relevant systems of record (ERP, property management system, CAFM, data warehouse, document management) and clarify where data lives, who owns it, and where integration boundaries sit.
5. Define functional requirements, success metrics, and acceptance criteria precisely enough that a Solutions Engineer or external vendor can deliver against them without rework.
6. Partner with the AI Solutions Engineer on scoping, hand-off, and post-launch measurement — closing the loop between projected and actual value.
7. Maintain a prioritised opportunity backlog and a clear, defensible point of view on sequencing.
What you bring
8. Real estate domain expertise (required) — several years working in or directly with real estate operations. You understand the difference between a service charge reconciliation and an operating expense recovery, what a rent roll actually contains, how leasing pipelines are managed, and how asset and property management interact day to day. You will not spend your first six months learning vocabulary.
9. Process analysis craft — fluency in BPMN, Visio, or equivalent, with a real portfolio of as-is/to-be process work behind you.
10. Business-case rigour — comfortable building cost models and ROI analyses in Excel from first principles, and equally comfortable defending the assumptions.
11. System-of-record literacy — working understanding of how ERP systems, property management systems, and data warehouses fit together, and where the boundaries between them sit. You don't need to be an integration engineer, but you should know what an API contract is, what master data means, and why it matters.
12. AI literacy — practical understanding of where modern LLMs, automation platforms, and agents genuinely add value — and where they don't. You can tell the difference between a use case that needs Copilot Studio, one that needs a vendor, and one that needs nothing at all.
13. Stakeholder skill — credibility with senior operators and finance partners, patience with end users, and the ability to translate fluently between them.
14. Languages — full professional fluency in German and English.
Nice to have:
15. A degree in business administration, industrial engineering (Wirtschaftsingenieurwesen), real estate / Immobilienwirtschaft, finance, or information systems. Equivalent experience is equally welcome.
16. Prior experience evaluating or implementing PropTech tools (ESG, CAFM, lease management, tenant experience, transaction platforms).
17. Exposure to data warehousing concepts and BI tooling (Power BI, Tableau, or similar).
18. Lean Six Sigma or comparable process-improvement training