I am a data scientist and a political psychologist¹ with a background in psychometrics, psycholinguistics, cross-cultural research, and modeling subjectivity.

I specialize in a diverse array of methods and techniques as a data practitioner. My expertise encompasses machine learning, deep learning, language models, and time series analysis. Additionally, I am proficient in statistical inference, particularly in the general structural equation modeling framework². My statistical toolkit extends to psychometric networks³, various network modeling applications, and survival analysis⁴.

My domain expertise is particularly relevant to political consulting, targeted communication, and public administration. My track record includes work on consumer behavior, customer segmentation, institutional culture, and mental well-being.

I’m currently taking a career break to improve my German and am open to work opportunities. I worked as a data scientist at BCW Global, Europe & Africa between 02/2022 - 05/2024. I served as the Turkish Language Group Leader in the European Commission Joint Research Centre’s ValuesML - Unravelling Expressed Values in the Media for Informed Policy Making project between 12/2023 - 05/2024. I am a former academic; I was an affiliated Postdoc Fellow at Bremen Graduate School of Social Sciences until 06/2024.

Some of my projects are available on ; browsing my portfolio website is another option. Feel free to connect on .

To find out more about me as the political psychologist, visit my academic website.

I occasionally make blogposts; read them here.

Footnotes

1. In case, you are wondering what political psychology is this, this & this can help form an accurate impression. Read two related blog post here and here.

2. This has been the workhorse of psychometrics for decades, with extended applications in causal inference. It is a flexible modeling approach for the statistical inference of not-directly-measurable concepts.

3. This has emerged as an alternative or supplementary method to structural equation modeling.

4. If you have a marketing background, read this as customer lifetime value or churn; sociologists call this time-to-event analysis or event history analysis. Whatever you call it, this is used to evaluate whether and when an event occurs.