Data Science

In this session of the Super Data Science Podcast, I chat with Ruben Kogel who has done some amazing data analytics in the startup space.

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/1

The Super Data Science Podcast: Big Data | Analytics Careers | Mentors | Success

SDS 001 : Self-serve Analytics, Data Science MBA and Managing a Team of Analysts with Ruben Kogel

We're excited to welcome a guest, Tim Head, who is one of the maintainers of the scikit-optimize package.  With all the talk about optimization lately, it felt appropriate to get in a few words with someone who's out there making it happen for python.  

Relevant links:
https://scikit-optimize.github.io/
http://www.wildtreetech.com/

Scikit + Optimization = Scikit-Optimize

If you work in tech, software or data science, there's an excellent chance you use tools that are built upon open source software.  This is software that's built and distributed not for a profit, but because everyone benefits when we work together and share tools.  Tim Head of scikit-optimize chats with us further about what it's like to maintain an open source library, how to get involved in open source, and why people like him need people like you to make it all work.

Open Source Software for Data Science

In this episode of the SuperDataScience Podcast, I chat with Head of Data Jaco Van Der Berg. You will talk about many different topics in the space of data such as data strategy, data security, data flow within an organisation and the single point of truth. You will also get to learn about managing and hiring for a data science team and will be able to gain lots of knowledge all about the structure of a data team. 

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/55

SDS 055: Building and Managing a Successful Data Science Team

As data science matures as a field, it's becoming clearer what attributes a data science team needs to have to elevate their work to the next level.  Most of our episodes are about the cool work being done by other people, but this one summarizes some thinking Katie's been doing herself around how to guide data science teams toward more mature, effective practices.  We'll go through five key characteristics of great data science teams, which we collectively refer to as "disciplined data science," and why they matter.

Data Science

Steffen Wiedenmann