Alexander Stubanus · Consulting & implementation
I build interfaces, automate recurring tasks and prepare data for reports and analysis. This helps you reduce manual work and base decisions on data you can trace and understand.
From clarifying requirements to technical implementation.
Technical expertise.
A business perspective.
How I can help
I help you automate recurring tasks, connect applications and analyse your data. Together, we establish where the work will be worthwhile.
Copying information, passing files around and triggering tasks by hand? I build workflows that work reliably together.
Your applications do their jobs. I make sure data flows between them, so information reaches the people and systems that need it.
If every report starts with a manual export, a shared data foundation is missing. I build data pipelines and reports your team can rely on.
Which trends are emerging? Which patterns matter? I turn your question into a sound analysis and develop models that support decisions.
Python & SQL · Microsoft Fabric & Azure · Power BI · Power Platform · Machine Learning & Language Models
A look at my work
Selected examples from freelance assignments, my employed roles and personal projects.
Freelance assignment · Finance
Business credit information arrived as Excel attachments by email and had to be processed manually. I automated the file processing and the subsequent write-off of the relevant debtor balances through a REST API.
The result: a connected processing pipeline replaces repetitive manual work.
The solution connects the email inbox to Excel data processing and write access to the target system. My contribution was the technical implementation of the automation pipeline.
Python · Excel Processing · REST API
From receipt to processing
Receive information
Prepare file contents for the workflow
Process data through the API
One workflow. Connected steps.
Employed role · Reporting
Disconnected business systems and manually prepared reports made it harder to manage a country subsidiary. I connected data collection, preparation and reporting into a shared pipeline.
Up-to-date management metrics, without manual intermediate steps.
The initial approach used automated downloads. These were later replaced by agreed data feeds from the providers. The data is brought together in Microsoft Fabric and analysed in Power BI.
Data Integration · Microsoft Fabric · Power BI
Employed role · Integration
An HR system and a learning platform needed the same information. I built the interfaces and data mappings and introduced automated data exchange.
Consistent information in both applications, with no duplicate maintenance.
The integration covers user profiles, qualifications, organisational structures and certification status. Synchronisation runs with error and change logs make the data exchange traceable.
APIs · Data Mapping · Synchronisation
Feasibility can be made tangible before a major investment: for example, with my demonstrator of a field service app featuring ERP integration and AI-assisted receipt capture.
Discuss a pilotData Science & Artificial Intelligence
My background in statistics and data science shapes how I work: from framing a precise question and choosing the method to critically assessing the results.
I help with statistical analysis, forecasting models and machine learning. Data quality, suitable baseline models and the limits of any conclusion are part of the work from the outset.
Discuss your questionAn example from my own projects
In FinAnalytics, I bring together transaction data from different banks. A random forest model categorises income and expenses, and a web application makes the results available for analysis.
A personal project that combines data integration, modelling and a working application.
The application recognises different bank export formats, combines them into a shared dataset and removes duplicates. A random forest model assigns transactions to main categories and subcategories. A Flask web interface makes it possible to analyse income, expenses and their development over time.
Data preparation, machine learning and a practical application work together.
How we work together
You can come with a specific task or a question that is still open. Together, we decide where to start.
We clarify the problem, examine processes and data, and assess the expected value.
Your outcome: a clear starting pointI describe the proposed solution, the effort involved and the technical requirements, giving you a basis for deciding whether to proceed.
Your outcome: a basis for decisionsThe solution takes shape in agreed stages. You can see progress and give feedback early.
Your outcome: a tested solutionDocumentation, training and handover make the solution usable in day-to-day work. We agree on any ongoing support.
Your outcome: a smooth transitionAn analysis, a pilot or a complete implementation: the scope depends on your project.
The person behind the solution
My background combines economics, statistics and data science with practical experience in finance and controlling. I understand the business questions behind a report as well as the technical challenges of producing reliable data.
I currently work as Head of Data, Automation & AI in the healthcare sector. I have also led a development team in management consulting for the healthcare sector. I support projects from requirements analysis and technology selection through a proof of concept (PoC) to implementation and rollout.
As a freelancer, I take on selected projects with a clearly agreed scope. You work directly with me, with transparent decisions and a handover your team can build on.
How we work togetherBefore our first conversation
I am particularly well suited to tasks that connect business processes, systems and data. This could be a single automation, a data analysis or a broader integration. In our first conversation, we establish whether my experience and availability fit your project.
No. A business question or a process that currently takes too much effort is enough to get started. The tools are chosen based on your requirements and existing systems.
After an initial assessment, we define the scope together. You receive a proposal setting out the services, deliverables and implementation assumptions. If technical questions remain open, a separate analysis or feasibility assessment may be a useful first step.
I take on selected projects that can be planned reliably. Before committing, we agree on availability, timelines and communication. We work mainly remotely, with coordination tailored to each project phase.
Documentation and knowledge transfer are part of the handover. We agree on responsibilities for operation, maintenance and possible further development to suit the project.
The next step
Tell me about your project. In a free, non-binding initial conversation, we clarify the starting point and a useful next step.
A few sentences about your task and the desired outcome are enough. Privacy notice (German).