I learned this programming language for advanced analysis in econometrics, biostatistics, spatial analysis, survival data analysis and data visualisation

Using as the main language for data processing, data engineering, machine learning, network analysis and spatial data science. I learned how to deploy Azure functionas, scraping data from websites, and use various APIs.

I learned Julia for projects where I faced performance issues. Further I developed machine learning, optimization and statistical modeling on demand

I stored the research data in our datalake, and used SQL to access prepare and transform data for researchers.

Postgres with its extensions is a useful tool that I used to process my projects to store spatial data and perform analysis.

DuckDB is one of the most useful tools that I had my hands on to store and access data for my projects. The inprocess and embedded nature of this tool made it the most suitable solution to my needs.

Experienced with git-based development. Mostly, use Github. Also, have experience in working with GitLab.

To store our document based data, I used MongoDB. Although I migrated all semi-structured data to other solutions, Mongo is still my number one for Json based solutions.

Econometrics knowledge is essential for my doctoral studies. These models are refined to accomodate economic assumptions, leading to more accurate results.

After learning this, I can be sure it also works on other systems!

The advanced models I learned outside of econometrics are from Machine Learning field that helped me to analyse and process data.

The three most important thing in Real estate are: Location, Location and Location. So I learned about the models and colutions this field offers.