Curious about the person behind the research?
I’m a researcher, teacher, and consultant combining causal inference, deep learning, and human-centered communication to turn uncertainty into action.
A mission rooted in curiosity
I grew from industrial engineering into causal machine learning because I love asking “Why?” even more than “What?”. Today I craft models that surface causal signals and communicate them in a way that builds trust with decision-makers.
Where you’ll find me
University of Hamburg
Research Associate and PhD candidate in Statistics. I study how multimodal data can strengthen causal inference and design reproducible workflows for Double Machine Learning.
Since 2023 · Hamburg 🇩🇪
Lab & classroom
I guide tutorials in statistics, machine learning, and mathematics—making concepts tangible with code, visual explanations, and open-source tools.
20+ sessions delivered
Industry collaborations
Previously at Philips and Siemens Gamesa I helped teams automate analytics pipelines, deploy Power BI ecosystems, and translate ML prototypes into operational tools.
Azure · PySpark · Data storytelling
Career timeline
Research Associate · University of Hamburg
Leading research on causal inference with multimodal data, co-developing the DoubleML framework, and supporting teaching in statistics and ML courses. 2023 – today
Data Science · Philips Medical Systems
Created Power BI reporting suites, PySpark workflows in Azure Databricks, and SQL assets in Synapse to optimize service planning. 2022 – 2023
Business Intelligence · Siemens Gamesa
Automated KPI dashboards, orchestrated MS365 integrations, and championed digital transformation initiatives for renewable energy teams. 2021 – 2022
Mathematics Instructor · Berufliche Schule Uferstraße
Developed tailored support courses that turned foundational math anxiety into confidence. 2019 – 2020
Academic track
Ph.D. Statistics
University of Hamburg, Department of Statistics. Focus on semiparametric models, causal inference, deep learning, and high-dimensional econometrics.
2023 – present
M.Sc. Industrial Engineering
University of Hamburg / HAW Hamburg. Thesis on “Causal Machine Learning with Deep Learning approaches” (Grade 1.0). Tracks in data science and energy engineering.
2020 – 2023 · Graduated 1.4
B.Sc. Industrial Engineering
University of Hamburg / HAW Hamburg. Built and stabilized a quadcopter as part of my thesis—my first major systems project.
2016 – 2020
What I bring to teams
Technical toolkit
Python, PyTorch, DoubleML, SQL, Azure Databricks & Synapse, Power BI, R, Spark, MLOps, APIs, reproducible research.
Collaboration superpowers
Translating between business questions and statistical design, leading student cohorts, coordinating cross-functional analytics squads, facilitating workshops.
Community & leadership
Former chair of the HWI student council representing 750+ students, orchestrating events for 30+ volunteers, and creating inclusive academic spaces.
Recognition
Hauke-Trinks-Award · 2nd Place
Honored by the Northern Institute of Technology Management for work connecting engineering rigor with human-centered innovation.
2020
Say hello
Email jan.teichertkluge@uni-hamburg.de · Call +49 40 42838-1517 · Office Moorweidenstr. 18, Room 0025.