Data Science Experts in Austria
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Meet FRATCH Experts in Austria, who have recently used Data Science
Chrisabel Prischl
Last position:
AI Systems & Product Strategy Expert at Webmeisterin
I build. I advise. I think in systems. After years leading digital transformation at scale — Accenture, BP, Lidl — I made a deliberate choice: trade platform dependency for structural independence. My focus is at the intersection of AI systems, product strategy, and venture thinking. I work with operators and founders who want to move fast without losing control — of their data, their stack, their direction.
Marcel Steger
Last position:
Senior AI Engineer - Python at Insurance Company
Project Tech Stack: Python, AWS, Azure, FastAPI, openai, pandas, unittest/pymock
Achievements:
- Engineered automated data extraction pipelines to transform complex Excel datasets into structured formats via LLM-driven workflows.
- Architected a generative slide-deck engine that translates natural language prompts into formatted presentation assets.
- Integrated advanced LLM capabilities with the OpenAI Response API, implementing sophisticated tool-calling and structured output logic.
- Developed and containerized scalable backend microservice using FastAPI, Docker, and OpenShift to host and serve agentic skills.
Shahram Fallahdoust
Last position:
Senior Product Owner at Elderly Neighbour Watch
Delivered a digital, non-profit neighborhood platform to connect older adults with volunteers for practical support and social companionship. Responsible for business analysis, requirement definition, platform evaluation and delivery of a locally scalable service solution focusing on AI-driven enhancements, data-based optimization and clear market positioning. Evaluated several low-code/business platforms including Odoo and Glide Apps and assessed monday.com as a CRM-like option before selecting Glide Apps for implementation. Implemented a non-native mobile and desktop application with Glide Apps and the web presence with WordPress. Tasks
- Gathering, analyzing and structuring business requirements for the product and service model
- Conducting market, target group and competitor analyses to position the offering
- Evaluating and selecting suitable low-code/business platforms for implementation
- Defining core user journeys, business processes and operational workflows for older adults, volunteers and administration
- Translating business requirements into functional requirements for profiles, task management, coordination, communication and notifications
- Guiding the implementation of the non-native mobile and desktop application in Glide Apps as well as the web presence in WordPress
- Preparing the business side for future AI-powered features such as intelligent matching and data-based optimization
- Ensuring compliance with GDPR requirements Results
- Successfully delivered digital support platform connecting older adults with volunteers
- Solid foundation for market positioning through market, target group and competitor analyses
- Delivered a functional non-native mobile and desktop application with Glide Apps and a supporting web presence with WordPress
- Established foundation for scaling and AI-based further development
Mario Tuta
Last position:
External Lecturer at FH Kufstein Tirol – University of Applied Sciences
- Study: Data Science & Intelligent Analytics
- Module: Big Data Processing
Nikolaus Jäger-Grassl
Last position:
Integration Architect at CECIL
Designed an API-first omnichannel integration, linking WhatsApp Business API with Salesforce Marketing Cloud to unify customer data across multiple platforms.
Automated customer onboarding and engagement workflows using Marketing Cloud Journeys, SSJS, and Azure Functions.
Developed a middleware layer to sync WhatsApp interactions with Sales Cloud for seamless customer experience tracking.
Georg Oberdammer
Last position:
CIO / CDO at TroGroup
- Design and execution of the transformation journey of IT & digitization and enablement of the further development of the group
- Development of the global IT & digitization strategy (motto: “ahead of the wave”) based on group standards and USP-driven digital solutions
- Definition of the digital strategy as part of the company’s 2030 strategy with a focus on the value disciplines “operational excellence,” “customer intimacy,” “product leadership”
- Design and implementation of a business-focused, global IT organization, including existing shadow IT parts
- Digital product development with a focus on IoT, data science, AI, software development (DevOps), cloud architecture, and Azure cloud services
- Initiation and ramp-up of the CoE for artificial intelligence and data analytics, including several agentic AI projects
- Definition and global rollout of the enterprise, infrastructure, and application architecture
- Cloud transformation including setup and execution of the global S/4HANA rollout, introducing new capabilities and modules
- Global business process standardization, automation, and end-to-end digitization within and across divisions
- IT/OT integration (shop floor, CAx integration)
- P&L responsibility and further development of digital marketing & sales channels, SEO/SEA, online product configuration, PIM/DAM, eBusiness/eCommerce systems
- Implementation of a global intranet portal and several digital solutions like Workday, Concur, Softconcis, Tacto, xFlow
- Further development of Salesforce beyond CRM into a sales backbone
- Support of M&A and divestiture
- Cyber security excellence, data protection, and NIS2 preparation
- Ramp-up of nearshore and offshore locations (Poland, India)
- Evaluation and implementation of business-value–driven IT innovation like RPA, business process AI, and low-code
- IT budgeting and controlling, KPI reporting, and negotiation of large IT contracts
- Global recruiting, people retention, and development
- Stakeholder management with executive management and heads of divisions
Armin Fanzott
Last position:
Head of AI & Data Science at Ascent DACH
- Lead architect for AI and ML projects including GenAI, LLM-based apps and forecasting solutions
- Guided customers through solution scoping, architecture design, and PoCs across various industries (Pharma, Insurance, Logistics, FMCG)
- Delivered production ML pipelines using Azure ML, MLflow, and MLOps best practices
- Responsible for effort estimation, delivery and staffing of 5 – 10 projects simultaneously
- Hiring manager for the data science and AI team and responsible for creating the technological offering and roadmap in the AI & Data Science space
- Built and scaled the AI/Data Science service offering from scratch to a high 6-figure annual revenue with 30+ successful deliveries and 20+ clients
- Regular speaker at AI and data science conferences and academic institutions
Christian Schön
Last position:
Commercial Manager/CFO at MEV Independent Railway Services GmbH
- CFO, authorized signatory, commercial managing director: finance, HR, IT & organization, funding
- Achieved reorganization and 100% growth in staff and revenue over four years while keeping fixed costs constant
- Improved a negative equity ratio to plus 30%
- Implemented a modern IT and reporting system
Rene Schakmann
Last position:
Head of Digital Services & IT at reet systems gmbh / THEOPHIL Holding GmbH
- Overall responsibility for IT, software development, and digital services of the company for brands such as Rosenberger, Rosehill, Burger King Austria (approx. 70 companies)
- Built the holding's lakehouse and data analytics platform
- Established and led the software development and IT department
- Established and led the operation (cloud-native AWS) of the B2B platform
- Connected IoT systems and developed models for predictive maintenance and production planning, data lake/lakehouse, and BI
- Preparation for ISO 27001 information security certification
- Technologies: Cloud, AWS, Java, Cypress, Angular, Python, Go
Kevin Lang
Last position:
Data Consultant at VBV Pension and Provident Fund Austria
Development of a structured framework and comprehensive guidelines for documenting business and audit processes in a regulated financial environment. Support for the standardization of process documentation to improve transparency, consistency, and traceability across all operational workflows. Contribution to defining documentation standards, templates, and governance principles for internal process management and audit readiness.
Discover over 15,000 top freelancers
Statistics of experts using Data Science
Aggregated from the professional profiles of matched freelancers.
Experience
19 years
Position duration
2.8 years
Positions per freelancer
13
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Manufacturing, Retail
Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
100%
Master's degree or higher
89%
Doctorate
11%
Certifications per freelancer
5
Most common languages
German, English, French
Speak two or more languages
100%
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Austria are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Average rates of experts in Austria using Data Science
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
Data work that informs decisions
Data Science turns raw data into forecasts, classifications, experiments, and clear business answers. It sits between analytics, statistics, and machine learning, and is used to explore patterns before teams decide what to build next. Strong specialists connect the question, the data, and the result.
Typical delivery
- Exploratory analysis and feature work
- Predictive models and evaluation
- Experiment design and A/B test analysis
- Reporting for product, finance, or operations
Tools and stack
Most projects use Python, R, SQL, Jupyter, pandas, scikit-learn, and visualization tools. Depending on the setup, specialists also work with notebooks, cloud data warehouses, and pipeline tools that move data from source systems into usable models. The right stack depends on how the team stores, cleans, and serves data.
When to bring in help
Companies often need freelance support when a project needs fresh analysis, a model prototype, or a fixed delivery window. It is also common when internal teams are busy, when a one-off use case needs a specialist, or when Austria-based stakeholders want someone who can work remotely and join local meetings when needed.
What strong specialists do
- Ask the right business question before coding
- Clean data without hiding its limits
- Test assumptions and explain trade-offs
- Document methods so others can reuse them
What to look for
Strong Data Science specialists show clear thinking, not just notebook skills. They can move from messy source data to a result that a company can trust, and they explain why a method fits the problem. For teams in Austria, that often means solid English, and sometimes German, depending on the reporting audience.
Frequently asked questions
What clients ask us most about Data Science — answered in short.
A strong Data Science expert turns raw data into analysis, forecasts, and models that help teams decide what to do next. That can include cleaning datasets, building features, testing hypotheses, and explaining results in plain language. The best specialists do not stop at a notebook; they connect the work to a real business question.
Data Science usually goes deeper than reporting or dashboard work. Analytics often focuses on what happened, while Data Science also asks what will happen and what action is likely to work. In practice, the two overlap, and many projects need both.
A solid Data Science specialist usually works with Python, R, SQL, and notebook tools such as Jupyter. Many also know pandas, scikit-learn, visualization libraries, and cloud data warehouses. For some projects, knowledge of notebooks, version control, and basic deployment matters just as much as model building.
Data Science freelance help is useful when a team needs fast analysis, a model prototype, or extra capacity for a specific project. It also helps when the problem needs a specialist with experience in experimentation, forecasting, or feature design. Many companies bring in outside expertise before they commit to a larger internal effort.
Yes, Data Science work is often well suited to remote collaboration because the main inputs are data, documentation, and clear review cycles. For teams in Austria, the best setup is usually remote delivery with regular check-ins, and on-site meetings only when close alignment is needed. Language expectations depend on the audience, so English is common, with German sometimes useful.
Data Science is the broader discipline: it covers analysis, data preparation, experimentation, and communication, not only prediction models. Machine learning is one method within that field. A freelancer who understands both can choose whether a simpler statistical approach or a more complex model is the better fit.
Data Science projects vary a lot, so the right level depends on the task. A clean exploratory study may need someone who is strong in statistics and storytelling, while a production model needs someone who can work with data quality, evaluation, and handover. The important part is proof of relevant project work, not a fixed number of years.
Look for clear problem framing, careful data handling, and results that can be explained without jargon. A good Data Science specialist shows how they validated the approach, what trade-offs they made, and how the work can be reused. If they can connect methods to business impact and still be precise, that is usually a strong sign.
The average hourly rate of freelancers in Austria who have used Data Science in their recent projects is 121 €, which corresponds to a daily rate of about 970 € based on an 8-hour working day.
Of the freelancers in Austria who have used Data Science in their recent projects, 100% hold at least a Bachelor's degree, 89% hold at least a Master's degree, and 11% hold a doctorate.
On average, freelancers in Austria who have used Data Science in their recent projects have 19 years of professional experience, with a single engagement typically lasting around 2.8 years.
The most common languages among freelancers in Austria who have used Data Science in their recent projects are German (100%), English (100%), and French (30%).
The most common industries among freelancers in Austria who have used Data Science in their recent projects are Information Technology (100%), Manufacturing (70%), and Retail (70%).
The most common business areas among freelancers in Austria who have used Data Science in their recent projects are Information Technology (100%), Business Intelligence (90%), and Product Development (70%).
Main locations of FRATCH Experts, who have recently used Data Science
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
Vienna Graz 
Vienna Request a free demo
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Philipp Thomaschewski
FRATCH CEO
