Ann-Kristin Vester

Lecturer & Data Scientist

Main focus: Data Science & Data Culture

Twitter handle: @akvdata


Languages: German, English

City: Karlsruhe

State: Baden-Wuerttemberg

Country: Germany

Topics: women in tech, data visualization, machine learning, artificial intelligence, data science, women in ai, data culture, data strategy

Services: Talk, Moderation, Workshop management, Consulting, Coaching, Interview

  Willing to travel for an event.

  Willing to talk for nonprofit.


I have been working as a data scientist in the IT and finance industry since 2016. The focus of my work is on using machine learning to make better decisions in the company, for example in selecting customers for advertisting or to increase customer satisfaction.

As a lecturer, I like to share my knowledge and experience, especially in the area of data strategy and data culture. I also give workshops and training courses in the programming language R and on how to get started in data science.

Besides my job, I volunteer on the board of CorrelAid e.V., a non-profit data science network. As a board member, I am responsible for educational work of CorrelAid.

My academic background is in the social sciences. My Master's degree in empirical political and social research especially helps me to see the people behind the data.

Examples of previous talks / appearances:

Informatica feminale 2022: Introduction to Data Science with R

Workshop at Informatica Feminale bw in Freiburg (2022). The following topics were covered:
- Set-up of RStudio, import and export of data

- Exploring data and basic statistical analyses

- Data Transformation and Manipulation with Dplyr

- Visualization with ggplot

- Introduction to supervised and unsupervised Machine Learning in R

- Basics of Text Analysis / NLP in R

This talk is in: English
Workshop "Beginner Session R" CorrelCon 2021

CorrelCon conference session about the first steps with R and RStudio, like reading data from a csv file, data wrangling and creating simple crosstables and plots. We will mostly use base R and packages from the tidyverse, which are a great starting point for beginners.

This talk is in: English