Three Ways Working as a Data Scientist at Spotify Made Me a Better Founder
Working in big tech is a standard route for aspiring founders looking to get valuable experience before launching their own thing. Product management and software engineering are the most commonly considered paths; however, data science is quickly emerging as a third path. Unfortunately, some overlook data science — it’s a shame because the role gives you valuable skills that are directly applicable to early-stage company building.
Before launching Slang.ai, I was a Senior Data Scientist at Spotify. Now, I’m over two years into my start-up journey (successful so far) and have learned a ton. Here are three reasons why data science helped me get where I am today:
1. I learned crucial fundamentals of product development
I participated in all aspects of product development, including design/prototyping, development, testing, launch, and optimization. Understanding how product development works is vital when taking a product from 0 to 1.
2. I built cross-functional knowledge and relationships
Data science is inherently cross-functional, which means you get to learn about basically all business functions and meet a lot of people. This was certainly true for me. Making connections with many different people at Spotify has helped — I’ve tapped several folks for advice as well as referrals when recruiting across multiple functions.
3. I went deep on deep learning
I specialized in machine learning, which helped me gain expertise in one of the most transformative technologies of our generation. Slang.ai relies heavily on machine learning technology that is powered by deep learning.
I highly recommend data science to any technically-oriented aspiring founders. If you’re interested in hearing more about my experience, reach out!
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