Claude Experts in Austria

Organizational Change Management for the strategic setup of a hybrid GBS rollout as part of a global, AI-driven Finance Transformation. End-to-end management of the OCM architecture in a highly complex on-, near-, and offshore partner setup [IN, PL, RO]. Successful completion of Phase 1 (Initial Strategy) and strategic pausing by the Executive Board after the early disclosure of critical vendor-side OPEX risks

• Systemic Baseline Assessment & Stakeholder Diagnostics: Evaluation of the global organization and analysis of the process landscape across 21 countries [AT, DE, CH, FR, UK, SI, RO, UA, RU, US, CD, CN, AR, MX, ZA, IN, JP] to precisely determine change requirements

• Architecting the OCM Strategy & Master Roadmap: Independent development of a comprehensive, AI-centered Change Roadmap for end-to-end management of all change initiatives across every project phase

• Data Quality & AI Agent Risk Mitigation: Auditing of Process Data Repositories (Celonis analysis); prevention of the ingestion of 58% synthetic training data to safeguard AI model reliability amid geopolitical supply chain tensions

• GBS Vendor BAFO Triage & Contractual Commitment: Critical review of Tier-1 vendor pitches and contractual commitment to a reduced Non-STP rate (from 7% to 4%) to avoid extreme manual rework with a planned FTE reduction (-63%)

• Executive Enablement & Board Alignment: Design of the GBS Transformation Executive Board Deck to strategically enable C-level executives and transparently present completely overlooked AI tokenization costs

• Targeted Change Communications & Engagement: Design and development of audience-specific communication measures to align the highly diverse, globally distributed stakeholder network

• Adoption Velocity & Resistance Measurement: Engineering of quantitative measurement tools (Pulse Check Survey) using Behavioral Dyads to identify resistance based on data and ensure sustainable success measurement

Results:

• Avoidance of disruptive misallocations: Stopping the ingestion of 58% synthetic AI-agent training data after discovering only 42% compatibility with existing processes, preventing critical GBS cascade errors
• Significant OPEX & effort reduction: Reduction of the Non-STP rate in Tier-1 vendor BAFOs from 7% to 4% alongside an impending 63% Finance-FTE reduction; avoidance of thousands of time-consuming manual correction processes
• 100% Delivery of the OCM architecture & ROI protection: Delivery of all OCM artifacts (Change Roadmap, Comms Plan, Executive Board Deck, Pulse Check Survey) and protection of ROI by identifying incalculable LLM runtime token costs

Independent practice serving clients in SAC-P and AI-enabled FP&A transformation, including financial model development for PE firm engagements, data cleansing with PowerQuery, workflow automation Claude Cowork, SAC-P scoping task-based assignments (Micro1.ai & Mercor.ai), and SAP partner network development.

• 2026 – Completed significant upgrade training for Positioning Business AI and SAP Cloud ALM Workshop (In-Person). Live Demos • SAC-P & Excel-Based Reports • Claude Partner • SAP Partner#: 1961209 (OE – Build)
• Fall 2026 – New effort to re-train/update past FI/CO, SAP BPC, SAP Platform to S/4 Finance & Core G/L Accounting
• 2026 – Upskilling for Transformation Toolchain. In-Person Workshops: Cloud ALM & SAP BTP • Joule Demo(s)
• 2025 – FP&A processes • Datasphere & Business Data Cloud • Team Workshops for AI • Toolchain & SAP Cloud ALM
• 2024 – Built key credentials on Deloitte S4 Experience • Group Reporting and SAC-P

• Project management in the PMO
• Further development of PMO and operational processes
• Development of templates and project documentation
• Management of a DACH/SOE-wide rollout project

I build. I advise. I think in systems. After years leading digital transformation at scale — Accenture, BP, Lidl — I made a deliberate choice: trade platform dependency for structural independence. My focus is at the intersection of AI systems, product strategy, and venture thinking. I work with operators and founders who want to move fast without losing control — of their data, their stack, their direction.

• AI strategy concept and implementation roadmap for an energy consulting company.
• Use-case matrix with nine application scenarios (including funding research, chatbot, initial AI consulting, topic radar), implemented as reusable Claude Code skills.
• AI strategy, use-case analysis / Claude Code Skills / n8n.

Technologies: Azure DevOps, Jira, Confluence, Office 365 (Teams, PowerPoint, Copilot, Excel, SharePoint, Forms, OneNote, PowerAutomate, Word), DataDog, Conceptboard, Python, AWS, Claude, Perplexity Methodology: Scrum

• Steering and supporting the organization in introducing Scrum and a SAFe-inspired quarterly roadmap and portfolio planning at program level.
• Servant leadership for Scrum teams and managers to achieve quarterly goals and measurably increase value creation for internal and external customers.
• Designing and building efficient communication and collaboration structures between multiple development teams and central stakeholders in the organization.
• Moderating and facilitating cross-functional workshops and management meetings to align on shared goals.
• Coaching leaders, Product Owners, and development teams on agile values, role understanding, and scaled ways of working (Scrum, SAFe, Business Agility).
• Removing structural obstacles at team and organizational level through targeted impediment management and escalation processes.
• Enabling teams to become more self-organized, accountable, and end-to-end responsible along the value streams.
• Individual coaching of key people (Product Owners, Chapter Leads, Scrum Masters) to strengthen their impact in the transformation program.
• Organization-wide identification, planning, and implementation of process, structure, and tool improvements to sustainably increase efficiency, throughput, and value creation.
• Close support for Product Owners in stakeholder management, business value prioritization, product strategy, roadmap planning, and effective collaboration with development teams.
• Introducing, governing, and scaling Azure DevOps as the central project and product management tool, including coaching the organization on usage, reporting, and alignment at all levels.

Achievements:

• Clear increase in visibility, transparency, and perceived value creation of the development teams within the overall organization.
• Noticeable improvement in communication between development, business, and other stakeholders.
• Optimization of work processes, workflow, and backlog structures, which reduced lead times, sharpened priorities, and sustainably increased team effectiveness.

Complete build of a B2B SaaS platform for recruitment agencies

• Multi-source job aggregation via ATS APIs
• AI-assisted career page scraping
• Rule-based and AI-assisted matching
• Credit-based monetization model with Stripe integration
• Live in production since July 2026

Tech stack

• NestJS
• React
• PostgreSQL
• pgvector
• Claude AI
• Prisma

• Set up and managed operational security in an upscale seasonal hotel. Responsible for staff training, risk analysis, emergency and access management, security documentation, and coordination with hotel management, employees, guests, partners and authorities.

• Took Dawnguard from initial product concept to a launched MVP within two months, building the backend platform and reducing cloud-environment scan times from approximately 40 minutes to under two minutes across 70 accounts.
• Designed and built the core resource discovery engine for Azure and AWS, enabling the frontend to visualise complex cloud environments and the AI to evaluate architectural patterns.
• Engineered distributed APIs and dynamic Cosmos DB schemas to support rapidly evolving product requirements and variable cloud-environment structures.
• Built the architecture-generation engine to support clients with 100+ cloud accounts and dynamically generate complete architectures containing approximately 25,000 resources.
• Developed custom data-generation tools that enabled the AI and frontend teams to simulate and test large-scale cloud architectures.
• Delivered backend features end to end by working with AI, frontend, and business stakeholders from technical design through implementation and testing.

Tech: AWS (Glue, Lambda, Redshift), Airflow, PostgreSQL, Python, PySpark, Metabase, Power BI

Delivered: Analytics-Ready Data Models • Legacy SQL to Cloud ETL Migration • Dynamic Pricing Engine

• Owned and evolved the company data warehouse end-to-end — from ingestion to transformation to analytics-ready dimensional data models on AWS Redshift.
• Collaborated with Analysts, Data Scientists, and business stakeholders to deliver scalable dimensional data models that enable self-serve analytics and streamline dashboarding in Metabase and Power BI.
• Architected end-to-end ETL/ELT pipelines on AWS (Glue, Lambda, Redshift) using Python and PySpark, orchestrated with Apache Airflow (MWAA) for reliability and observability.
• Defined and enforced data quality standards and governance practices across pipelines and the core data layer.
• Led migration of legacy SQL infrastructure into scalable AWS Glue pipelines with distributed PySpark processing, eliminating bottlenecks and reducing downtime.
• Developed a dynamic pricing engine applying automated promotional discounts based on occupancy rates, competitor pricing, and location performance tiers.
• Designed schema mappings to ingest MongoDB data into structured relational systems (Redshift/PostgreSQL).

Project Tech Stack: Python, AWS, Azure, FastAPI, openai, pandas, unittest/pymock

Achievements:

• Engineered automated data extraction pipelines to transform complex Excel datasets into structured formats via LLM-driven workflows.
• Architected a generative slide-deck engine that translates natural language prompts into formatted presentation assets.
• Integrated advanced LLM capabilities with the OpenAI Response API, implementing sophisticated tool-calling and structured output logic.
• Developed and containerized scalable backend microservice using FastAPI, Docker, and OpenShift to host and serve agentic skills.

• Project Lead, Sr. BI Expert, Data Scientist, Automation Engineer for Marketing Analytics | Customer Insights (retail, e-commerce)
• Product Manager: Asset Metadata Ingest & Provide
• Product Owner Business Intelligence – responsible for 2 teams: cloud data engineering, data warehouse (logistics)
• Product Owner for setting up a reporting platform on Azure & Power BI (finance)

• BSS system implementation for B2B / transformation of the central B2B system landscape
• End-to-end business responsibility for defining, structuring and prioritizing key B2B business processes as part of a complex BSS transformation.
• Work in an agile, SAFe-like setup with multiple teams involved, along with regular coordination with business, IT, solution design and architecture.
• Translation of business requirements into implementable epics, features, user stories, process models and acceptance criteria as the basis for technical implementation.
• Close collaboration with solution design and architecture to assess technical dependencies, interfaces, data flows and system impacts.
• Management of target process design as the basis for implementation in Infonova BSS.
• Interface management between business departments, IT, architecture, development and operational units, including facilitation of cross-functional workshops.
• Ensuring process consistency, governance, decision-making capability and business acceptance as part of the system implementation.

• Architected enterprise AI strategy delivering 25% cost reduction through multi-LLM platform integration (Claude, OpenAI, Gemini) with intelligent routing and fallback optimization
• Drove operational excellence achieving 85% reduction in manual documentation and 3x faster campaign production through AI workflow automation and agent deployment across Slack and Microsoft Teams
• Established AI governance framework from ground up, implementing EU AI Act compliance, data redaction protocols, and safety filters aligned with DPIA standards
• Scaled AI adoption through structured onboarding programs, developing departmental workflows with secure access controls and comprehensive audit trails
• Implemented advanced RAG systems using Elasticsearch, Vertex AI, and Azure AI Foundry to improve knowledge access and output reliability
• Managed delivery through OKR framework coordinating cross-functional squads across 6-week project cycles to ensure strategic alignment and measurable results