Natural Language Processing Experts in Hamburg

• Reviewing functional and technical requirements from a testing perspective
• Creating test cases and automated tests to validate requirements
• Performing manual and automated functional, end-to-end, and regression tests
• Documenting test results and tracking defects
• Using models like GPT-4, BERT, and Hugging Face Transformers for automated test case generation, analysis of test results, and improving test coverage, including bias checks and security reviews
• Techs: MS Office, Jira, Zephyr, Confluence, Tosca, stakeholder communication, Agile, Kanban, Scrum, OpenAI API, Hugging Face, PyTorch, LangChain.

Self-directed exploration of agentic AI development methods, taken from idea to a working, publicly usable application

• Built an interactive planning tool for modelling retirement withdrawals and tax strategy using an agentic AI (vibe coding) development approach – demonstrating self-directed investigation of new AI-assisted development methods
• Delivered live, tax-aware spending projections and adjustable user inputs; shipped as a free, install-free browser application built in Python, with attention to usability for non-technical users

• 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.

Relocation from the UK to Germany and structured transition period focused on consolidating executive experience in data platforms, analytics, and AI, and formalising decision-centric data and AI frameworks, including governance models in preparation for the next long-term leadership role.

• 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.

• Delivered 3 video and multimodal evaluation projects, shipping 80+ high-complexity video with 90% QA pass rate
• Improved annotation workflow and QA gates, reducing average handling time by 15% and rework by 23%

• Responsible for sales, including marketing, and financial controlling.
• Gathered almost six years of experience in project management, project development and structural engineering consulting.
• Applied expertise to support business development and administrative management.

• Build data pipelines for raw and curated data layers using AWS S3, Glue, Athena, and Lake Formation
• Establish CI/CD using GitHub Actions or GitLab CI with CodePipeline
• Prototype models into demo APIs packaged with Docker, versioned with Git, added basic tests with pytest, and assist deployments on AWS SageMaker Endpoint
• Perform exploratory data analysis and feature engineering with pandas and PySpark; track experiments in MLflow or Weights and Biases
• Design and execute A/B tests to optimize user engagement and drive data-informed decisions

• Situation: A medium-sized, traditional company – technologically advanced but outdated in its market presence. Lacking a guiding vision for the next generation.
• Goal: A clear positioning for the future: differentiation from global competitors, a modern brand presence that builds internal pride and external visibility.
• Solution: A vision that unites everyone – including positioning and a new corporate design. Translating the DNA into the website, copy, translations, and merchandise – a brand that is not only designed but lived.
• Result: Uncertainty became a clear vision. Today, Wester presents itself as a modern family business that shows its stance with the claim "A grain shapes the future".

• Attained AWS Certified Cloud Practitioner certification.

• Mastered Rust through self-study, including books, online courses, and open-source contributions.

• Developed a serverless web application using AWS (RDS, Lambda, Polly, Amplify) and TypeScript/React/D3, managed infrastructure with CDK.

• Continuously stayed updated with industry trends through self-education, webinars, and workshops, exploring Data Mesh and FastAPI.