About
felix@felixlennert.xyz · LinkedIn · Download CV (PDF)
Professional Summary
I am a quantitative researcher and analyst with a Ph.D. in Computational Social Science and seven years of applied experience across academic, consulting, and industry contexts. My work combines rigorous statistical methodology – causal inference, NLP, and machine learning – with practical problem-solving for clients in education, research, and industry. I have delivered analytical projects ranging from organizational performance dashboards to multilingual NLP classification pipelines, consistently translating complex findings into clear recommendations for decision-makers. With cross-cultural experience across Europe and the United States, I bring both methodological depth and effective communication to every engagement.
Selected Experience
Freelance Data Science Consultant | Boston, MA | 2024–present
Providing analytical consulting services to domestic and international clients in education, survey research, and industry.
Engagement 1 – Organizational Performance & Growth Strategy
Conducted performance analytics for a U.S.-based professional education company. Developed interactive dashboards to identify underperforming course offerings, informing strategic portfolio restructuring. Designed data-driven marketing campaigns using social media and web analytics that increased enrollment. Delivered AI-focused curriculum strategy resulting in five new course offerings.
Engagement 2 – Multilingual Survey Analytics
Designed and implemented NLP classification pipelines for open-ended survey responses across four languages for a Scandinavian research institution. Validated automated classifications against expert-coded benchmarks, achieving human-level accuracy (F1: 0.91–0.98). Co-authored two manuscripts currently under peer review. Delivered reproducible analysis code and publication-ready visualizations.
Engagement 3 – Industrial Sector Classification & Market Intelligence
Developed an LLM-based classification pipeline for a European client to categorize companies by industrial sector and verify ISO certifications. Implemented quality-control workflows combining regex-based filtering, LLM classification, and manual validation. Delivered a clean, structured database ready for client decision-making.
University Lecturer | Leipzig University & University of Regensburg | 2018–2026
Designed and delivered 17 courses on data science methods – including web scraping, NLP, machine learning, and statistical modeling in R and Python – to 500+ students at senior and master level. Co-supervised 10+ Bachelor’s and 3 Master’s theses. See Teaching Materials for full course list.
Data Analyst | Linköping University | 2020–2021
Provided research support for publications in Nature Human Behavior and Science Advances, including large-scale text data collection (80M+ forum posts) and machine learning analysis in R and Python.
Education
Ph.D. in Sociology · ENSAE, Institut Polytechnique de Paris · 2026
Dissertation: computational analysis of ideological, affective, and lifestyle polarization across France, Germany, and Sweden. Visiting Scholar, Duke University (2024, 2025).
M.Sc. in Computational Social Science · Linköping University · 2021
B.A. in Political Science · University of Regensburg · 2019
Technical Skills
Quantitative Analysis: causal inference (DiD, synthetic control, PSM), econometrics, regression modeling, A/B testing, Bayesian methods
Machine Learning & NLP: text classification, clustering, transformer models (sBERT, HuggingFace), LLM pipelines (LangChain, Ollama, Anthropic API)
Programming: Python (pandas, scikit-learn, transformers, numpy), R (tidyverse, ggplot2, RShiny), SQL
Communication & Dashboarding: RShiny, PowerBI, Tableau, Looker, reproducible reporting, technical writing