Title | Time | Room | Teacher |
---|---|---|---|
NEW: How to become a Data Scientist? - In Person | 07.06.2023 09:00 - 16:30 (Wed) | Hittorfstr 16, 14195 Berlin | Dr. Anne Löchte, Dr. Florian Kornrumpf |
Before booking a workshop, please make sure that you can attend for the entire duration and save the dates. When participants do not show up or cancel on a very short notice, other interested parties are denied a chance to participate.
Participation
For doctoral candidates of all disciplines. Participants should be familiar with gathering, cleansing, analysis and interpretation of data. Not necessary is a background in IT!
Objectives
'Data driven decision making' is an established standard in modern company culture. The demand for employees with experience in data - that is gathering, cleansing, analysis and interpretation of data - is high and still rising. At the same time, the field is differentiating into sub-specializations: 'Data science', the most popular buzzword, is just one in a larger array of job profiles which require diverse skills and competencies. The field 'Data X' is highly interesting for PhD students with a wish to switch out of an academic career who are well-versed in working with data. Students of many different fields are able to turn their skills into practice, such as Linguistics, Psychology, Social and Neuroscience, Marine Research and others.
Many PhD students are lacking knowledge of the existence and meaning of job titles such as Data Scientist, Data Engineer or Business Intelligence. What does a data scientist do in their day-to-day work? What qualification profile should an analytics engineer have? How does one go about entering the job market? Despite the need on the job market, the switch can be challenging. Multi-stage application processes that test technical competencies alongside teamwork and other social skills are quite common.
Content
In this workshop, the participants:
- get acquainted with typical tasks and requirements in the Data X field
- learn which profile fits them best
- analyze their own skills and match them with the specific data job they are looking for to find what might be missing
- get to know the typical layout of hiring processes as well as concrete knowledge about which skills are relevant in which stage of the hiring process
If there are free spots, we also allow postdocs to participate.