Show Notes:

• (2:15) Jan discussed his undergraduate experience studying Business Administration and Economics from Goshen College in Indiana.
• (3:48) Jan went over his first job out of college: working as a Strategy and Enterprise Intelligence consultant at the EY office in Berlin, a Big 4 consulting firm.
• (6:09) Jan talked about his decision to pursue a part-time Master’s degree in Computer Science at the Trier University of Applied Sciences while working at EY.
• (7:21) Jan covered the most useful graduate courses during his Master’s degree, including Advanced Programming and Distributed Systems.
• (9:05) As part of his program, Jan did his thesis with the Scout24. In fact, he even wrote a blog post offering a glimpse of what it’s like to be a data scientist at Scout24.
• (12:31) Jan discussed the benefits of taking deep learning online classes from Andrew Ng’s deeplearning.ai platform.
• (15:52) Jan is also a mentor and ambassador with deeplearning.ai, in which he gives feedback on the educational content, discusses new product ideas, and writes forum entries.
• (19:30) Jan discussed his current projects at Carmeq GmbH, the Berlin-based innovation vehicle of Volkswagen AG.
• (21:22) Related to his work at Carmeq, in the blog post “The State of Self-Driving Cars for Everybody,” Jan outlined the 6 main infrastructural problems of self-driving cars for the masses. We discussed these problems in finer detail.
• (30:52) Jan gave a curated list of 5 mindset-chasing books that helps him become a better data scientist, referring to his article “Top 5 Business-Related Books Every Data Scientist Should Read.”
• (38:32) Jan shared the 5 pitfalls that young data scientists can stumble upon in their first job, referring to his article “The Power of Goal-Setting in Data Science.”
• (44:38) Jan emphasized the importance of using Google’s goal-setting method OKRs (Objects and Key Results) to set a data science project up for success, referring to his article “The Power of Goal-Setting in Data Science.”
• (48:32) Jan explained the AI Project Canvas, which answers the most pressing questions about the outcome and resources needed for an AI project.
• (51:50) Jan went over the importance of learning business basics for data scientists.
• (56:30) Referring to his post called “Becoming a Level 3.0 Data Scientist,” Jan discussed his current career trajectory as well as skills that he is looking to develop.
• (58:20) Jan gave his advice for data scientists to make a leap from an individual contributor to a manager.
• (01:02:04) Referring his post called “The Secrets to a Successful AI Strategy,” Jan gave his advice for data scientists to collaborate productively with their counterparts in product management and business operations.
• (01:02:55) Jan shared his opinions on the technology and data community in Berlin.
• (01:05:00) Closing segment.

His Contact Info:

• Medium
• LinkedIn
• Twitter
• GitHub

His Recommended Resources:

• Deep Learning Specialization from deeplearning.ai
• Federated Learning
• Lex Friedman’s “Deep Learning for Self-Driving Cars” class taught at MIT
• Nassim Taleb’s “Skin In The Game"
• Nassim Taleb’s “Black Swan"
• Peter Thiel’s “Zero To One"
• Eric Ries’ “The Lean Startup"
• Daniel Kahneman’s “Thinking, Fast and Slow"
• Richard Rumelt’s “Good Strategy, Bad Strategy"
• John Doerr’s “Measure What Matters"
• AI Project Canvas
• William Oncken’s “Managing Management Time"
• Google AI and DeepMind
• DeepMind: The Podcast hosted by Hannah Fry
• Hans Rosling’s “Factfulness"

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