Description

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.

Industry field of expertise

Languages

German
Native or bilingual
English
Fluent

Workplace preferences

Remote only

Primarily works remotely

Datanumerix
Data Science & Simulation Consultant
CONSULTING AND AUDITS
October 2020 - Today (5 years and 8 months)
Göttingen, Germany
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