AI Advisor | 15 years in AI

5/2024 – 11/2025

• Build 3 PoCs: Inbound Mgmt. Automation, Calls transcription, classification & summarization & 2nd Level Knowledge Mgmt. Chatbot increasing operational efficiency
• Created a business case and management decision proposal coordinating all relevant stakeholders to get board level approval for the development of an enterprise-wide rollout
• Designed & implemented a local AI solution for the Inbound Management case incl. Hardware/GPU scoping for local processing, setup of a local LLM endpoint, MLOps automation, IaC (Terraform/Bicep), network security, GDPR-compliant data handling, and comprehensive observability / monitoring

Data Science, DevOps, Vektordatenbank, Confluence, Jira, Python, Microsoft Powerpoint, Datenschutz, It-Governance, IT-Projektleiter, Strategisches Management

3/2024 – 7/2024

• Conducted a 1st party data activation assessment
• Identification of data strategy and governance gaps and options to improve them (short- & long-term)
• Designed & implemented a central data platform, enabling their data-driven business strategy with prioritized data analytics & science Use Cases

Konzeption (IT), BI-Spezialist Data Warehouse, Big Data, Data Science, Datenarchitekt, Marketing, Microsoft Powerpoint, Strategische Unternehmensplanung

6/2023 – 4/2024

• AI strategy framework specification (as-is assessment, to-be specification & roadmap)
• Designed & implemented an LLM-Chatbot leveraging internal documents for the legal research team with plans for additional Use Cases and productization

Konzeption (IT), Data Science, IT-Projektleiter, IT-Strategieberatung, Microsoft Powerpoint, Workshop - Kundenorientierung

4/2023 – 6/2024

• Built production-grade RAG system for legal research using LLMs on Azure stack, enabling natural language querying of complex regulatory and contract documentation
• Engineered scalable deployment for 1,500+ users with MLOps automation, IaC (Terraform/Bicep), network security, GDPR-compliant data handling, and comprehensive observability / monitoring
• Established AI governance framework and trained cross-functional teams (Legal, HR, Finance) to replicate success across departments

Data Science, IT-Projektleiter, Cloud (allg.), Solution Architekt, Governance

10/2022 – 2/2024

- Architected and delivered enterprise data platform that became the foundation for company-wide analytics and data science initiatives, enabling marketing, trading optimization, and operational intelligence
- Established data governance framework with clear ownership, quality standards, and access controls—transforming fragmented data silos into a trusted, self-service analytics environment
- Enabled 10+ business-critical use cases across trading, marketing, and supply chain optimization through scalable data infrastructure and standardized data models

Confluence, Jira, Konzeption (IT), Microsoft Powerpoint, Sicherheitskonzept, Cloud (allg.), Datenarchitekt, Datenmodelierung, Datenschutz, IT-Projektleiter, IT Sicherheit (allg.), Schulung / Training (IT)

8/2022 – 11/2025

Legal Knowledge Management solution | German Energy Trader
• Built production-grade RAG system for legal research using LLMs on Azure stack, enabling natural language querying of complex regulatory and contract documentation
• Engineered scalable deployment for 1,500+ users with MLOps automation, IaC (Terraform/Bicep), network security, GDPR-compliant data handling, and comprehensive observability / monitoring
• Established AI governance framework and trained cross-functional teams (Legal, HR, Finance) to replicate success across departments

Agentic AI solutions & platform | German Energy Trader
• Identified and validated Finance automation opportunities through cross-functional workshops, creating business-case-backed roadmap that secured C-suite investment in autonomous AI capabilities
• Delivered working agentic AI solutions that autonomously execute financial processes (invoice verification, anomaly detection, report generation), shifting Finance from transaction processing to strategic analysis
• Built reusable AI platform infrastructure enabling safe, governed agent deployment: semantic knowledge foundation, orchestration layer managing multi-agent workflows, enterprise tool connectivity, risk guardrails preventing hallucinations/errors, real-time monitoring

AI transformation ignite | Swiss Commodity trader
• Assessed AI maturity across technology, organization, and processes—identifying capability gaps and quick-win opportunities that shaped executive investment priorities
• Defined AI vision and 3-year strategic roadmap through cross-functional ideation workshops, prioritizing 20+ use cases by business value and technical feasibility
• Led vendor evaluation for horizontal AI tools (knowledge management, document intelligence, process automation), managing demos and selecting solutions that accelerated time-to-value vs. custom development
• Established AI governance framework (decision rights, risk controls, technical guardrails) enabling secure, compliant enterprise adoption while maintaining innovation velocity

Central Data Analytics Platform | German Energy Trader
• Architected and delivered enterprise data platform that became the foundation for company-wide analytics and data science initiatives, enabling marketing, trading optimization, and operational intelligence
• Established data governance framework with clear ownership, quality standards, and access controls—transforming fragmented data silos into a trusted, self-service analytics environment
• Enabled 10+ business-critical use cases across trading, marketing, and supply chain optimization through scalable data infrastructure and standardized data models

Data Literacy and Upskilling Program | German Energy Trader
• Conducted organization-wide data literacy survey (300+ respondents) and identified critical skill gaps blocking data-driven decision-making
• Created and launched "Data Champion" curriculum that trained 30+ employees as internal evangelists, multiplying data capabilities across the organization
• Led pilot cohort through 6-month learning journey, establishing scalable model for enterprise-wide data upskilling and culture change

First Party Data Activation Assessment | German Energy Company
• Analyzed why company couldn't activate customer data for personalization by assessing it’s Business Data & IT capabilities spanning vision, architecture, teams, processes, and legal/privacy frameworks
• Translated findings into actionable roadmap: closed 12 critical gaps, aligned stakeholders on priorities, and secured executive sponsorship for €2M+ transformation investment
• Architected future-state solution enabling customer segmentation, next-best-action recommendations, and campaign optimization while ensuring GDPR compliance and data security

AI Governance & Enablement | German Energy company
• Created enterprise-wide AI usage policy governing 1,400 employees' interaction with AI tools—balancing innovation enablement with data protection, IP security, and ethical AI principles
• Architected EU AI Act compliance framework including system classification methodology, conformity assessment processes, documentation requirements, and ongoing monitoring mechanisms
• Designed pragmatic incident management approach tailored to AI-specific risks (hallucinations, bias, data leakage)—defining roles, response procedures, and remediation workflows
• Led change management through targeted workshops and training for business users, technical teams, and executives—translating complex AI governance into actionable practices

IT-Projektleiter, Langchain, Softwareanforderungsanalyse, Anforderungsspezifikationen, Change Management, Docker, Git, Governance, Jira, Microsoft Azure, Power Bi, Python, System Design, Tensorflow

1/2021 – 7/2022

End-to-End implementation of AI solutions (concept, prototype, productization in cloud platform, automatic dashboard integration):
• Internal marketing campaign performance (CTR) modeling, monitoring & alerting
• System Incident Monitoring using user session data
• Marketing campaign performance modelling (identification of success factors for activated orders, forecasting and what-if analysis)
• DQ Monitoring solutions for all crucial data sources and attributes
• Model validation: cancellation forecast model (Bayesian structural time series model, qualitative & quantitative validation)

Specification of an AI Strategy:
• Use Case elicitation & prioritization with business various departments
• AI Maturity assessment (processes, organization, data, skills, technology)
• Gap Analysis and roadmap specification to implement the AI strategy

Concepts specifying the AI strategy building blocks:
• ML /AI Life Cycle (business understanding, data preparation, modelling, development, operations)
• Data Quality Monitoring framework
• Operating model, Roles and responsibilities,
• Model Monitoring framework
• Coding guidelines and best practices
• AI product deployment and operations guidelines

Anforderungsspezifikationen, Docker, Git, Governance, Gradient Boosting, Jira, Langchain, Microsoft Azure, Power Bi, Python, Softwareanforderungsanalyse, SQL, Strategische Unternehmensplanung, System Design, Tensorflow

2/2020 – 3/2021

Implementation of a financial due diligence automation solution for a Global semiconductor company:
• Conception (e.g. solution architecture, financial outlier detection, nlp)
• Financial statement analysis (web scraping of companies P&L and balance sheets, anomaly detection to identify risks and opportunities)
• Annual report analysis (BERT Q&A explaining reasons for outliers as well as FDD standard Q&A report)
• GUI (UX specification, mockup design, implementation by freelancer)

Data Science, IT-Projektleiter, Vektordatenbank, Confluence, Jira, IT-Strategieberatung, Microsoft Powerpoint, Finanzanalyse

7/2019 – 3/2021

Implementation of a financial due diligence automation solution for a Global semiconductor company:
• Conception (e.g. solution architecture, financial outlier detection, nlp)
• Financial statement analysis (web scraping of companies P&L and balance sheets, anomaly detection to identify risks and opportunities)
• Annual report analysis (BERT Q&A explaining reasons for outliers as well as FDD standard Q&A report)
• GUI (UX specification, mockup design, implementation by freelancer)

Implementation of an industry trend monitor analyzing structured and unstructured data:
• Web scraping (financial data and google news for various companies)
• Topic identification and modelling using vector space models
• Sentiment and time series analysis to identify topics trend
• Output visualization (Tableau as well as design of a webpage incl. UX specification; implementation by a web agency)

Implementation of a production planning solution for a business unit carve out at a Global pharma company:
• Supply chain resp. network analytics to identify production constraints and value flow complexities
• Sales resp. demand forecasting using time series analysis
• Production planning taking production as well as regulatory constraints into consideration while ensuring continuous market supply for all global brands and markets
• Scenario analysis (e.g. impact of corona on local markets)

Docker, Git, Governance, Jira, Microsoft Azure, Power Bi, Python, SQL, System Design, Tensorflow

7/2019 – 9/2020

Implementation of a production planning solution for a business unit carve out at a Global pharma company:
• Supply chain resp. network analytics to identify production constraints and value flow complexities
• Sales resp. demand forecasting using time series analysis
• Production planning taking production as well as regulatory constraints into consideration while ensuring continuous market supply for all global brands and markets
• Scenario analysis (e.g. impact of corona on local markets)

Analyst Logistik, Datenanalyse, Datenarchitekt, Datenmodelierung, IT-Projektleiter, IT-Strategieberatung, Jira, Power Bi, Produktionsplanung und -steuerung (PPS), Scrum

10/2018 – 6/2019

• Led enterprise data governance transformation as Project Lead, establishing foundation for data-driven decision-making across global operations
• Defined operating model with clear data ownership, stewardship roles, and cross-functional accountability spanning central functions and decentralized business units
• Redesigned governance committee structure to accelerate decision-making established Data Council, domain-specific working groups, and escalation mechanisms
• Orchestrated stakeholder alignment through comprehensive communication strategy engaging 50+ system owners managing customer data
• Scoped and launched pilot program across 5 critical systems and 200+ data attributes, demonstrating governance value and building momentum for enterprise rollout
• Developed 18-month transformation roadmap with phased implementation, quick wins, and change management approach adopted by executive leadership

Confluence, Governance, It-Governance, IT-Projektleiter, IT-Sicherheitsberater, IT-Strategieberatung, Jira, Microsoft Powerpoint

9/2017 – 6/2019

Design and end-to-end implementation of a customer lifetime value model at a Swiss health insurance company:
• Project lead
• Conception (functional and technical) incorporating client specific income (upselling, customer churn, customer network), cost and risk potentials in a holistic DCF framework
• Implementation of a prototype (various regression and classification models as well as a wrapper model) in R
• Specification of use cases along the insurance customer journey
• Implementation of the prototype in the customer´s operational systems (SQL Server Mgmt. Studio 2016)
• Know How transfer to client experts incl. MLOps operating model (process and responsibilities per role)
• Change Management for the whole company

Design of a data governance framework for a German automotive:
• Project lead
• Definition of roles and responsibilities
• Redesign of the committee structure
• Definition of a communication plan towards customer data relevant central units as well as decentral units
• Assessment and specification of a pilot scope (systems and attributes) for an initial implementation of the governance framework
• Development of a transformation roadmap

Design of a target operating model for data analytics department of a Global retailer:
• Project lead
• Specification of roles (internal and extern)
• Specification of data analytics process
• Mapping of roles to responsibilities
• Specification of committee structure incl. communication and escalation process
• Executive training: AI in Banking (via Management Circle)

Docker, Git, Governance, Jira, Microsoft Azure, Power Bi, Python, SQL, System Design, Tensorflow

9/2017 – 8/2018

Design and end-to-end implementation of a customer lifetime value model at a Swiss health insurance company:
• Project lead
• Conception (functional and technical) incorporating client specific income (upselling, customer churn, customer network), cost and risk potentials in a holistic DCF framework
• Implementation of a prototype (various regression and classification models as well as a wrapper model) in R
• Specification of use cases along the insurance customer journey
• Implementation of the prototype in the customer´s operational systems (SQL Server Mgmt. Studio 2016)
• Know How transfer to client experts incl. MLOps operating model (process and responsibilities per role)
• Change Management for the whole company

Data Science, Datenanalyse, SQL, IT-Projektleiter, Scrum, Jira, Solution Architektur, Schulung / Coaching (allg.), Schulungskonzepte

1/2011 – 1/2017

Implementation of master data system for market data at a German development bank
• Project lead
• Agile project management (Scrum)
• Conception (processes, data model, interfaces)
• Configuration and implementation of a standard software (Markit EDM)
• Test and release management

Local implementation of a group-wide regulatory AMA model for the quantification of operational risks at a major European bank:
• Implementation (calculation, sensitivity analysis, stress testing) in R
• Design and implementation of a prototype for the capital allocation of the regulatory risk capital in R
• Support during validation

Validation of a tools for the scaling of loss potentials in the context of OpRisk Risk Assessments at a major European bank:
• Analysis of methods as well as analysis of the implementation
• Validation of underlying assumptions (graphical and numerical) in R
Conception and implementation of a credit risk early warning system at a German automotive bank:
• Business / IT concept
• Implementation of an analysis prototype in SAS
• Implementation of a validation prototype in SAS

Feasibility study for the implementation of credit risk early warning system at an Austrian banking group:
• Development of a reference architecture
• Specification of requirements, the logical data model as well as data structures
• Roadmap and cost estimation

Conception and implementation of a prototype for the time series analysis of market risk factors at a major European bank:
• Business concept incl. case study
• Implementation and test of a prototype in R
• Technical training of the internal employees

Test of a regulatory reporting solution regarding correctness and completeness for the following COREP templates:
• Credit Risk (C07 - C13)
• Own funds (CA01 - CA05)
• Large exposure (LE1 - LE5)
• Leverage ratio (C40 - C45)

Conception and implementation of various classification and regression analysis prototypes in R for internal business development
• Residual value analysis for a German automotive
• Identification of relevant loss given default risk factors for a German state bank
• Comparison of the accuracy of various machine learning algorithms in relation to an in-house solution
• Twitter sentiment analysis

Docker, Git, Governance, Jira, Microsoft Azure, Power Bi, Python, SQL, System Design, Tensorflow