DataSentics in “So You Want to Be a Data Scientist?” Podcast

Our colleagues talking about day-to-day data science work in a podcast

Petr Michal
Jul 27, 2020 · 2 min read

Our colleagues Nikola Valešová and Petr Míchal were guests on the episode of “So you want to be a data scientist?” podcast. 🎉

The podcast is dedicated to aspiring data scientists, data engineers, and machine learning engineers. It shows the day-to-day life and work of professionals in this area.

In approximately 30 minutes, Mısra Turp asked about the professional journey of Nikola and Petr, their previous jobs, and why they wanted to be data scientists.

Mısra asked questions about various aspects of datascience work, what techniques are useful to organize tasks, and how much of their work represents meeting the clients.

Both Nikola and Petr had a lot of things to tell at the question of what they like about their job. 😃

Because they work on different projects, they could capture a variety of projects in DataSentics. Nikola works these days on online marketing and Petr specializes in computer vision.

It was a great time with Mısra since our colleagues could reveal what their normal day looks like and it hopefully helps the others, who are willing to start their job in the world of big data.

Listen to the podcast yourselves and find out what Nikola and Petr do every day and much more about work in DataSentics!

Thank you for reading up to this point. If you have any further questions or suggestions, feel free to leave a response. Also, if you have a topic in mind that you would like us to cover in future posts, let us know in the comments below.

DataSentics

An agile machine learning and cloud data engineering boutique

DataSentics

Make data science and machine learning have a real impact on organizations across the world — demystify the hype and black magic surrounding AI/ML and bring to life transparent production-level data science solutions and products delivering tangible impact and innovation.

Petr Michal

Written by

DataSentics

Make data science and machine learning have a real impact on organizations across the world — demystify the hype and black magic surrounding AI/ML and bring to life transparent production-level data science solutions and products delivering tangible impact and innovation.

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