Data Visualization Expert in Germany

Working Environment

• Insurance / Claims Management (Property, Liability, Automotive)
• REST-based ClaimAPI with Guidewire ClaimCenter

Scope

• Further development of the internal REST-based ClaimAPI with Guidewire ClaimCenter as the backend and various portals/front-end offices as clients, and with the following objectives: + increased AI-supported claims processing outside of Guidewire ClaimCenter + and support for all lines (property, liability, automotive).
• Further development of automated claims processing

Activities

• Interfacing IT & Business
• Design activities with documentation in Confluence, Jira: + Requirements engineering (functional and non-functional) + Design of REST endpoints and coordination with interface partners (esp. AI-colleagues) + Identification, design and evaluation of alternative solutions (moving away from a monolithic approach toward fine-grained endpoints, with code reuse across all lines if possible) + Creation / refinement of product backlog items in Jira, i.e. epics, user stories and tasks, incl. alignment with developers & POs during (pre-)refinement sessions + Using AXA Secure GPT when creating / refining user stories (description, acceptance criteria) and designing REST endpoints + Estimation and prioritization of user stories and tasks during Sprint Planning sessions + Coordination and support during the implementation of Product Backlog items + Driving decision making with preparation and presentation of decision-making documents
• Quality assurance: + Test management, including test case creation using Xray in Jira + Test execution using Bruno as REST client and in Guidewire ClaimCenter + Submission of test artifacts for PO approval + Analysis of production bugs

Methods Big Room Planning (aka PI-Planning in SAFe), Scrum, BPMN, EPK, UML, ERM, DDD

Tools / Tech Stack Teams, Confluence, Jira with Xray, OpenAPI/Swagger, REST, JSON, XML, MS Office, Bruno, GitHub repository (reading), Guidewire ClaimCenter, AXA Secure GPT (AXA's in-house GenAI solution based on Azure OpenAI)

Development of AI and traditional models to analyze medical and patient data, including medication analyses, diagnosis analyses, forecasts, procedure analyses, dosage analyses, comorbidity analyses, prescription analyses, patient potential analyses, referral profile analyses, and prescription analyses. Analyses in the field of Real World Evidence.

Healthcare IT, pharmaceutical industry

Tasks, responsibilities:

• Gathering customer requirements
• Planning the subproject
• Designing and defining KPIs
• Designing and developing models and visualizations of results using customer dashboards
• Developing and implementing data warehouse adaptations
• Deriving recommendations for action

Methods, technologies:

• Simulation
• Artificial intelligence
• Python
• R
• SQL
• Microsoft Power BI
• Amazon Web Services
• Elasticsearch
• PostgreSQL
• Databricks
• Multivariate statistics

Further Development of the Integrated Capacity Management Platform InKa

Rail Infrastructure

• Power BI shared datasets and reports via DirectQuery on Amazon Redshift (timetable, construction and capacity data)
• Automated report testing with Playwright in Docker containers, version control with GitLab
• Concept and implementation of user communication (information page, changelog, known bugs)

Initial Situation:

The integrated capacity management platform (InKa) is a monitoring and analysis platform for data from timetable and capacity management: customer orders, infrastructure, timetable operations, construction, as well as route capacity and width. The data is stored and linked in a structured data warehouse. This makes it possible to create complex KPIs across different source systems and display current and future route utilization as well as construction activity across the network. The goal is to improve strategic, medium-term and intra-year planning and provide users with easy access to capacity management analyses.

Measures:

• Enablement: Introduction of Power BI with training and workshops for development teams.
• Consulting & Design: Problem analysis, concepts and solution consulting for reporting requirements; implementation of reporting solution plans.
• Data Model: Development of shared datasets with DirectQuery on Amazon Redshift and import tables; DAX measures for utilization and capacity KPIs.
• Development: Data analysis, data transformation and visualization in Power BI; extension and migration of business applications to Power BI; AI-supported development in VS Code with GitHub Copilot.
• Test Automation: Automated testing of Power BI reports with Playwright; setup of the test environment in Docker containers.
• User Communication: Concept and implementation of a central information page with hot news, changelog and known bugs, access from reports with report filters, updates via Power Automate.
• Deployment: Management of Power BI Deployment Pipelines across the DEV, TEST and PROD environments.
• Agile Working: Work in an agile team according to SAFe (Scaled Agile Framework); refinement of user stories and features including effort estimates in Jira; version control with Git and GitLab.
• Quality & Documentation: Reviews for quality assurance, error analysis and resolution, technical documentation in AsciiDoc and Confluence.

Technologies: Power BI, DAX, Power Query, DirectQuery, Amazon Redshift, Git / GitLab, Deployment Pipelines, Playwright, Docker, AsciiDoc, Power Automate, Jira, Confluence, VS Code with GitHub Copilot, SAFe

Results:

• Capacity management KPIs from multiple source systems combined on one platform
• Transparency regarding current and future route utilization and construction activity across the network
• Easy access to analyses for users
• Automated regression testing of Power BI reports
• User communication implemented: central information page with hot news, changelog and known bugs, directly accessible from the reports

Overall business responsibility for a program-wide initiative to create a central, authoritative data foundation for business customer master data (contacts and locations) within an IT service management transformation program.

• Managed the Epic portfolio from exploration through launch; prioritization and quarterly planning in a SAFe environment
• Aligned business units, architecture, and IT delivery around a shared vision and clear rules for data ownership (Data Governance)
• Prepared and secured scope and key decisions with program leadership, including deliberate descoping
• Managed risks, dependencies, and escalations; reported to program leadership and the PMO
• Developed the 2027 roadmap as a basis for budget and portfolio planning

Result: a clear MVP scope, key decisions made, and a 2027 roadmap. The program continued after handover without any loss of knowledge.

• Supported monthly and annual closing activities
• Checked incoming invoices for formal and factual accuracy
• Posted incoming invoices
• Contact person for internal departments on accounting matters
• Created and maintained vendor master data
• Processed open items
• Took on additional accounting-related special tasks
• Managed the functional mailbox
• Performed payment runs

Training and knowledge transfer – Accounts Payable:

In addition to the tasks above, I was responsible for training and transferring knowledge to 8 employees of an external service provider in India who took over the accounts payable activities:

• Conducted structured training and practical guidance throughout the accounts payable process
• Trained employees in checking and posting incoming invoices, including formal and factual checks
• Taught vendor master data maintenance, open-item processing and payment runs
• Trained employees in using the functional mailbox and communicating effectively with internal departments
• Explained accounting procedures, controls and company-specific accounts payable requirements
• Conducted “Training on the Job” using practical posting cases and real business transactions
• Supported the team in independently carrying out accounts payable processes and resolving accounting questions
• Checked the quality and accuracy of work results and provided continuous feedback and coaching
• Supported the transfer of accounts payable processes to the external service provider and ensured structured knowledge transfer and an orderly handover
• Supported a smooth transition by documenting processes, clarifying responsibilities and ensuring consistent application of accounting requirements

Software: JDE, ELO, SAP Concur

• Development of scalable backend applications with C#/.NET and Java
• Design and implementation of distributed microservice architectures
• Development and integration of REST APIs for industrial applications
• Development of modern web applications with React, Angular, and TypeScript
• Implementation of MQTT-based communication solutions
• Integration of industrial protocols such as OPC UA and Modbus TCP
• Development of batch, process control, and HMI components
• Containerization and deployment of applications with Docker
• Conducting code reviews and supporting architecture decisions
• Close collaboration with Product Owners, QA, and interdisciplinary teams
• Analysis of business requirements and implementation of technical solutions
• Further development of existing software architectures with a focus on maintainability and performance

Technologies: C#, .NET, ASP.NET Core, Java, C++, React, Angular, TypeScript, Vue.JS, MQTT, OPC UA, Modbus TCP, Docker, GitLab, MariaDB, MySQL, Linux

• Taught ML, BI, and Big Data to Master's students.

Tech: Python, Power BI, SQL, ML, SnowflakeDB, databricks, MS Fabric, MongoDB, LLM

Evidence-led health intelligence platform turning published research into personal health protocols. It scores 430 habits, foods, and supplements against the studies behind them, and moves the score when the evidence moves. Built solo.

• Built the daily ingestion pipeline across PubMed, bioRxiv, and medRxiv: 43,000+ papers from 3,400+ journals processed into 230,000+ typed evidence claims, each one traceable back to the study it came from.
• Designed the six-factor evidence scoring model and the public changelog behind it, so no recommendation ever appears without the papers underneath it. 23,000+ grade changes recorded and explained to date.
• Shipped an entity information model connecting every intervention to its mechanisms, biomarkers, and outcomes: 118 biomarkers with region-specific reference ranges, 77 mechanisms, 32 graded outcomes.
• Built the personalisation layer: blood panel ingestion that reads lab PDFs with a vision model and corrects results for draw time against the user's wake anchor, plus Oura, WHOOP, and Withings integration for daily readiness context.
• Operate eleven specialised review agents over the corpus and codebase, covering paper curation, retrieval quality, health-claim compliance across EU and US regimes, and security.
• Shipped the Evidence Assistant, a RAG assistant that answers from the claim database and cites the underlying papers, plus a B2B practitioner tier, an Expo React Native app, and localisation across 3 languages and 7 markets.

Stack: Next.js 16, TypeScript, Supabase, pgvector, Anthropic Claude, Vercel, DeepInfra.

• Supporting the International Web Presence of the BA (IntWeb) project in the area of quality management, with the aim of taking responsibility for the quality of processes and project results while considering BA standards. The main objectives of the project are to give professionals abroad a quick overview of their opportunities for moving to Germany and to enable them to take the necessary steps consistently and with digital support by providing access to services.

• Defining the general guidelines in the QA handbook

• Summarising test results in QA reports for PLA

• Analysing project results for improvement opportunities

• Quality management of requirements analysis (particularly processes, methods, and tools)

• Ensuring compliance with SERA requirements

• Creating a cross-project test concept

• Agreeing on sprint completion reports

• Formal review of work results in accordance with requirements and/or the project plan

• Contact person for internal audit, external audits by auditors, or BRH (Federal Court of Audit)

• Technologies: JIRA, Confluence, MS Office, GitLab, Kubernetes

• Overall responsibility for platform transformation across ERP, CRM, PIM and AI-supported process automation
• ERP transformation: Introduction and migration to Microsoft Dynamics 365 Business Central
• CRM & Growth Stack: Implementation of HubSpot as the central CRM and platform for lead and marketing automation
• Product data & Commerce Enablement: Introduction of an ePIM to scale Category Management and digital Commerce processes
• AI-supported process automation: Design and introduction of agent-based AI workflows to automate processes in Business Services, Accounting, Tender Management and Marketing
• Building a scalable platform organization consisting of Product Development, DevOps, UX, Cloud Engineering and Corporate IT
• Introduction of modern product and portfolio governance (e.g. OKRs, portfolio boards, value-based roadmaps) to manage technology-driven initiatives
• Harmonization of heterogeneous system landscapes and transformation into a modular, scalable platform architecture (ERP, CRM, PIM, integrated customer journeys)
• Coaching and development of Product Owners, Tech Leads, Delivery Managers and UX teams in building a scalable product organization

• Detecting fraud patterns and implementing effective anti-fraud rules while maintaining acceptable false positive rates to ensure a balance between safety and a frictionless user experience
• Supporting ideation and roll-out of new trust and safety features to the platform to block fraudulent activity and increase user awareness for fraud
• Supporting Product, Development and Customer Support with BI reports and further guidance to identify and fight fraud and policy violations

Service & Release Management:

• Initially solely responsible for operational customer service and release management for three months until the team was scaled up
• End-to-end release communication: coordination with development and hosting, client-specific release notes, distribution management, dispatch and follow-up of feedback
• Participation in release acceptance through hands-on testing; close alignment with release planning
• SLA-driven case handling in ServiceNow; ticket processing times tracked as a KPI for improving service speed
• Central interface between federal authorities, specialist departments and development; escalation management, internal dailies and monthly client reviews

Process Development:

• As-is/to-be process analysis and visualisation (draw.io, BPMN), incl. interfaces to adjacent departments
• Service-oriented process handbook with clearly defined roles and responsibilities
• Walkthrough and optimisation of service processes in the ITSM framework together with IT
• Incident workflows between ITSM tools and Jira; Jira project configuration and shared dashboards
• Improvement management: quick clarification with development or structured submission with tracking in Jira

Enablement & Knowledge Management:

• Handbook for GSB 11 customer management incl. ServiceNow handling, work instructions and client templates
• Self-service documentation, step-by-step guides and client-specific service records in Confluence
• Supporting client authorities through the transition from rollout to live operations
• Onboarding a colleague from the GSB 7 team: knowledge transfer between teams, shared best practices and short-term reinforcement of the GSB 11 team
• Establishing post-rollout interviews to evaluate the transfer of responsibilities between departments
• Evaluation of internal AI agents for incident communication and guide creation

• This project involved extraction of intelligence data to support report writing for a company that provides geopolitical, global, commercial intelligence. The data have been gathered from a number of resources (interview transcripts, online data, internal documents), and then a knowledge base has been build from it. This was the basis of a complex RAG system, that was evaluated against a golden dataset. Agents have been used to find out the contradicting intelligence, the statements supporting each other, and to store back the generated knowledge.

Used: Python, RAG, LangGraph, LangChain, deepeval, MCP

• Client — Podimo ApS (podcast & audiobook streaming): build the finance reporting layer on BigQuery + dbt + Airflow, including the core revenue-transaction fact tables used across finance reporting.
• API automation: design and build a BigQuery → Airflow → Microsoft Dynamics 365 Business Central REST-API pipeline to automate sales-invoice posting, with idempotency and master-data sync between systems.
• Delivery: sole engineer on the engagement — requirements, modelling, orchestration and stakeholder communication with the client finance team, end to end.