Dr. Patrick Krennmair
Senior Data Scientist and Researcher
Vienna, Austria
My background spans research, consulting, and team leadership at the intersection of technology and global development. I began in academia, using geo-spatial machine learning to explore poverty and inequality. That foundation in digital transformation and international development still shapes how I think today. Most recently, I’ve led teams working on generative AI. I bring an interdisciplinary mindset and a strong passion for AI to every project I take on.
Research Interests
Generative AI
Exploring cutting-edge AI technologies and their practical applications
Machine Learning & Statistics
Predictive methods and computational statistics for data-driven insights
Economic Development
Applied econometrics and small area estimation for emerging markets
Digital Transformation
Bridging traditional economics with modern data science approaches
Education
Dr.rer.pol. in Applied Statistics
2019 - 2022Freie Universität Berlin
MSc in Economics
2016 - 2018Universität Wien
MA in Development Studies
2016 - 2019Universität Wien
BSc in Statistics
2015 - 2018Universität Wien
BSc in Economics
2013 - 2016Universität Wien
Professional Experience
My journey in data science, statistics, and consulting spanning academia and industry
Senior Data Scientist and Team Lead
CurrentI lead a high-impact team focused on advancing Generative AI capabilities within Dynatrace CoPilot. My work combines hands-on data science with leadership and mentoring. I drive the deployment of LLM-powered applications into production, ensuring scalable and reliable performance in cloud environments. Collaboration across product and engineering and research teams is central to aligning our technical innovation with business goals.
Key Achievements:
- Team Leadership & Mentoring
- Generative AI & LLMs
- Cloud-native Deployment
- Agile Collaboration
Data Science Consultant
Leading data science initiatives and digital transformation projects for enterprise clients. Specializing in machine learning implementation, statistical analysis, and AI strategy consulting.
Key Achievements:
- Implementing generative AI solutions for business processes
- Developing predictive models for operational optimization
- Leading cross-functional teams in digital transformation projects
- Providing statistical consulting for strategic decision making
PhD Researcher & Statistical Consultant
Conducted doctoral research in applied statistics and provided specialized statistical consulting through the fu:stat unit to researchers, institutions, and businesses.
Key Achievements:
- Conducted research in small area estimation techniques
- Published peer-reviewed papers on computational statistics
- Applied econometric methods to real-world problems
- Designed and analyzed surveys and experiments
- Developed custom statistical solutions for clients
- Supervised and trained students and clients
Technical Expertise
AI/ML & Advanced Analytics
Core AI & Machine Learning
Programming & Data Engineering
Languages & Infrastructure
Research & Statistical Methods
Statistical Analysis
Professional & Consulting
Leadership & Communication
Publications & Research
My academic contributions, automatically updated from my Google Scholar profile.
Flexible domain prediction using mixed effects random forests
P Krennmair, T Schmid
Journal of the Royal Statistical Society Series C: Applied Statistics 71 (5 …, 2022
Analysing opportunity cost of care work using mixed effects random forests under aggregated census data
P Krennmair, N Würz, T Schmid
arXiv preprint arXiv:2204.10736, 2022
Tree-based machine learning in small area estimation
P Krennmair, N Wurz, T Schmid
The Survey Statistician 86, 22-31, 2022
The R package SAEforest
P Krennmair, MP Krennmair
R package version 1 (0), 2022
Analysing opportunity cost of care work using mixed effects random forests under aggregated auxiliary data
P Krennmair, N Würz, T Schmid
Journal of the Royal Statistical Society Series C: Applied Statistics, qlaf031, 2025
A Framework for the Estimation of Disaggregated Statistical Indicators Using Tree-Based Machine Learning Methods
P Krennmair
Flexible domain prediction using mixed effects random forests
T Schmid, P Krennmair
Otto-Friedrich-Universität 71 (5), 2022
Die Macht der Schulden: Interdisziplinäre Perspektiven auf die sozioökonomischen Implikationen von Staatsverschuldung im Kontext der Sustainable Development Goals
M Thalhammer, P Krennmair
Shrinking Spaces: Mehr Raum für globale Zivilgesellschaft, 171-208, 2020
Die Macht der Schulden: Interdisziplinäre Perspektiven auf die sozioökonomischen Implikationen von Staatsverschuldung im Kontext der Sustainable Development Goals
P Krennmair, M Thalhammer
Get In Touch
I'm always interested in discussing new opportunities, research collaborations, or consulting projects. Let's connect and explore how we can work together.
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© 2025 Dr. Patrick Krennmair, Vienna.
Passionate about data science, statistics, and digital transformation.