Beschreibung

I am a mathematician and data scientist with a strong background in applied mathematics and statistics.

My work focuses on developing analytical and data-driven solutions that connect mathematical theory with real-world applications. I combine solid statistical thinking with hands-on implementation in Python and R to uncover insights, build models, and communicate results clearly.

I have experience in applied research and public-sector projects, contributing to data analysis, modeling, and evaluation tasks. My approach is driven by curiosity, precision, and a passion for transforming complex data into meaningful conclusions.

Core competencies:

• Data analysis and visualization in Python (pandas, matplotlib, seaborn)

• Forecasting and statistical modeling in Python and R (scikit-learn, statsmodels)

• Experimental design and survey data analysis

• KPI development and performance evaluation

• Simulation and mathematical modeling for decision support

• Reproducible workflows and clear reporting (LaTeX, Tableau)

I am hands-on in every step of the data science process, from data exploration and model design to interpretation and presentation. Whether it is research, analytics, or predictive modeling, I aim to deliver solutions that are both rigorous and practical.

Branchenexpertise

Sprachen

Deutsch
Muttersprachlich oder zweisprachig
Englisch
Verhandlungssicher

Arbeitsortpräferenzen

Nur remote

Führt Projekte hauptsächlich remote aus

Datanumerix
Data Science & Simulation Consultant
BERATUNG & AUDITS
Oktober 2020 - Heute (5 Jahre und 8 Monate)
Göttingen, Deutschland
I have been working in data science and applied mathematics since 2020, combining mathematical reasoning with applied research and data-driven analysis.

My academic and professional experience bridges mathematics, simulation, and data science. During my master’s studies in Mathematics (Data Science focus), I worked on several analytical and simulation-based projects that connected theoretical modeling with real-world applications.

Since 2023, I have been working as a research assistant in applied data science, focusing on the evaluation and modeling of mobility and transport systems. My recent work includes two major research projects:
• Population Synthesis for Agent-Based Modeling (MATSim), developing data-driven synthetic populations using statistical imputation (Hot Deck, IPF) and integrating them into large-scale simulation environments.
• Evaluation of Demand-Responsive Transport (DRT) Service Quality, designing and applying quantitative KPIs for comfort, reliability, and technology performance based on real-world operational data.

I also have experience with experimental design and behavioral data analysis using oTree, combining statistical interpretation with reproducible workflows in Python and R.

Across all my projects, I focus on reproducibility, clarity, and analytical depth, transforming complex data into actionable insights through mathematical and statistical modeling.
Mathematics Data science Python (Programming Language) Simulation Modeling Statistics