Data Science Experts in Hamburg

• Implementing cross-industry applications with LLMs
• Developing cloud infrastructure for clients
• Implemented end-to-end data pipeline to deploy models in real time
• Managed overall IT system administration and desktop support

• Building an AI & Data Consultancy Practice with the goal of helping European companies adopt Artificial Intelligence and modern data platforms
• End-to-end further development of a production system using modified coding agents (OpenCode). Tech stack: Kubernetes, Argo, Keycloak, Typescript, Grafana, GitOps, DevOps, Playwright
• Internal research project on the use of coding agents in the field of mathematical logic for creating formal models. Use of Cursor IDE and Codex, Codex CLI. Architecture design, quality control and refactoring, as well as writing code and tests. Repository (open source) available pre-launch
• Research on the role of mathematical logic as a formal language that connects IT and AI with business processes
• Project lead for collecting and deploying parking recommendations for rail vehicles with significant savings potential based on real-time data in a mobility and transport company
• Project lead for collecting and distributing process measurement points for real-time control in a mobility and transport company
• Deputy application owner for an app used for communication in the dispatching and provision of rail vehicles

• Remodeling of the system architecture for an Azure-based platform aimed at rapid development of new functionalities
• Modeling of a staging concept for the fulfillment of diverse customer and QA needs
• Creation of requirements for, and oversight of, a proof-of-concept supplier project for a Flutter app with highly advanced BLE functionalities
• Comparison of multiple observability platforms for feasibility and requirements fit within the project environment
• Creation of a mobile app architecture based on domain-driven architecture
• Position of technical advisor and accountable solution architect for two development teams
• Execution of architecture reviews and alignment of changes with architectural expectations
• Skills & Technologies: Microsoft Azure , App Services, NodeJS Mono-repository, microservice architecture, domain driven design, self contained systems, requirements engineering, CI/CD, DevOps, API design, solution architecture

Freelance work for a large German family office

Built and further developed a modular B2B SaaS platform for professional wealth management and family offices, alongside freelance delivery of production-ready AI, data management, and automation solutions for the wealth management sector.

• Developed an AI governance framework for regulated finance and asset management workflows, aligned with DORA, BaFin-related governance expectations, and data protection requirements, including role definitions, access levels, and decision rules.
• Designed an agentic system with a locally operated open-source language model, including Qwen2.5 via Ollama, for secure querying of an asset database through text-to-SQL-to-text workflows.
• Built AI-supported analysis and reporting capabilities that generate structured answers, tables, and charts from asset data, with domain validation through resolver logic and RAG elements.
• Developed production-grade data import workflows for financial service provider data from CSV, PDF, and API sources, including validation, plausibility checks, and reconciliation with existing asset data.
• Solved the asset matching problem without a cross-system primary key through multi-stage validation rules and human-in-the-loop approvals.

Results:

• Secured EUR 250,000 in SaaS revenue in 2024, exceeding the forecast by 20%.
• Acquired family office clients with EUR 1.6bn in assets under management.
• Reduced manual effort for the largest client by approx. 3 days per month through automated data import and reconciliation processes.
• Reduced operational error risk through structured data validation, multi-stage asset matching, and human-in-the-loop approvals.

• Successfully completed a 3.5 month data science course, earning the ‘Certified Data Scientist’ title from XDi, Germany (AZAV certified).
• Covered supervised and unsupervised machine learning algorithms.
• Covered natural language processing using Python.

• Designed and implemented an initial product management framework

• Created a process for prioritizing the product roadmap with internal stakeholders, considering business impact, resources, and technical feasibility

• Led the migration to a product discovery tool to improve transparency and cross-team collaboration

• Served as a liaison between tech and business teams

• Managed data-driven sustainability projects for the largest key account, including implementing regulatory reporting (ISO 14083) on greenhouse gas emissions

• Delivered complete data integration across 20+ source systems, coordinating onboarding and translating business requirements into technical specs for the development team

• Enhanced the client's emission tracking and reporting accuracy through data quality analyses and identifying optimization opportunities

• Co-founded the German chapter of the International Women's Coffee Alliance, contributing to strategic vision development and organizational structuring for international development initiatives
• Optimized internal workflows and reduced administrative overhead through systematic process analysis and documentation
• Designed and implemented governance frameworks and data governance standards to support ESG compliance and transparency requirements for NGO operations
• Developed comprehensive data strategy to enhance data quality, transparency, and reporting capabilities across international stakeholder network

• Hands-on product and portfolio analyses with actionable recommendations
• Skilled in consulting, concept development, and agile project management
• Technical leadership & team empowerment – for smooth agile delivery with foresight and guardrails

• Lead developer of Prof. Valmed, the first LLM-powered medical device (utilising RAG on a medical corpus of 2.5M+ documents) to receive a CE certification.
• Designed and implemented cloud-native MLOps infrastructure for ENBW’s energy trading analytics division, enabling scalable deployment and monitoring of predictive models.
• Architected end-to-end testing and validation frameworks for AI/ML systems, ensuring quality, compliance, and robustness in critical and regulated applications.
• Conducted professional training on AI testing, EU regulatory frameworks, and quality assurance for production AI systems.

• Founded, built, and led a company
• Led up to 6 FTEs to achieve company and investor goals
• Strategic management: mission, USP, goals, strategy & roadmap
• CX management: customer-focused products, offerings, and touchpoints
• Marketing & sales: B2C marketing, B2B sales, market research

• Architected and deployed LLM based AI agents, RAG pipelines, and vector search solutions for decision support across retail banking department.
• Developed and shipped robust AI pipelines with guardrails, error handling, monitoring, and fallback logic ensuring high reliability outcomes and compliance with data privacy.
• Developed and deployed ML models to identify transactional anomalies, improving fraud detection and risk assessment in high-volume datasets for credit risk modelling.
• Built, evaluated and fine-tuned ML models to generate propensity scores for customers used to drive personalized targeting campaigns for credit cards and personal finance/loan products.
• Developed an NLP pipeline using BERT embeddings and spaCy NER for SMS/email analysis and customer query logs.
• Trained machine learning models using Isolation Forest to classify user behaviour and detect anomalies.
• Extracted, cleaned, enriched and feature engineered datasets from different sources to build feature stores that powered ML model training.
• Led development of dashboards using Power BI, Grafana, and Prometheus to monitor model performances, KPI trends, and marketing metrics.
• Built multi-touch attribution models using logistic regression and time-decay weights to evaluate lead quality.
• Developed scalable ETL pipelines from CRM, T24, SAP, and ERP, supporting millions of monthly transactions.
• Integrated testing and CI/CD workflows for robust data pipeline deployment.

• Conducted research on fluidized bed reactors, applying machine learning methods for process monitoring and predictive maintenance.
• Developed reproducible workflows for high-temperature process experiments, improving data reliability and lab efficiency.
• Collaborated with cross-disciplinary teams to integrate AI models into traditional engineering research.

• Overall responsibility for project management, analytics, AI & Data Science, database management, and web development (24 FTE).
• Implemented and established AI-driven analytics and AI work tools, increasing efficiency per FTE by over 20%.
• Developed and launched a planning and forecasting platform, increasing error tolerance by over 60%.
• Introduced an ERP software, reducing required FTE by 50%.