Quitting my VC Job To Learn Data Science and Machine Learning. How will I learn?

By Kimberly Cook |Email | Sep 24, 2018 | 24996 Views

Yesterday was my last day at Point Nine Capital.

When I joined Point Nine two and a half years ago, I knew nothing about Venture Capital. Originally from Belgium, neither I nor my friends had exposure to this world. But I had this sudden urge to experience it firsthand and I started to look around for an opportunity.

I would be lying if I told you that I knew who or what Point Nine was at the time I applied. Having read their job offer, however, I just loved their tone. So I bought a book that was basically VC for Dummies, spent dozens of hours getting familiar with the space, read 1,000,000 blog posts from the Point Nine teamyes, I also thought that they had ghostwriters at that time (we don't) - and was finally offered a role after no fewer than 5 Skype interviews.

My first day was a bit rough as I first met the team during an off-site and managed to get stuck on a rock during a climbing activity. Yes it was hot, yes there was a partner getting seriously nervous behind me, and yes I always manage to put myself in such situations!

I kept climbing the VC rock ever since with the Point Nine crew behind me and enjoyed it every moment. I feel super fortunate that I had the opportunity to work with such a great team and such amazingly enthusiastic entrepreneurs. I learned a lot and still think that this job is one of the best in the world.

So why the f*** would I leave such an amazing job?

When I look back to the companies that got me the most excited over the last two and a half years, I realised two things:

1) There was often some data magic/machine learning involved,
2) They had some sort of positive impact on society.

Some examples:

  • Vintra, which is a video analytics platform allowing public and private investigators to leverage video to solve crimes, save lives and secures assets. Data = video surveillance footage, impact = safer world.
  • Corti Labs, who provide live diagnostic assistance, analysis of emergency call data, and training modules for call takers. Data = emergency calls, impact = save lives.
Machine learning is not new and has definitely been overhyped. However, I still believe that amazing things can be done with it. Whenever I looked into a new company, I was truly interested in understanding how the technology works in detail. However, the nature of the VC job means that I could just not afford to spend the time I wanted to. So I thought that I would just learn about it in the evenings and during the weekends.

This was six months ago and was the peak of inflated expectations. Three months ago, disillusioned, I realised I won't make it. One month ago, at the slope of enlightenment, I decided to quit and do it full time for couple months. From January 1st, I'll start to study full time and hopefully will reach the peak gradient of productivity.

How will I learn?
I am looking at learning everything online so I can do it from everywhere.

Comparing courses and asking people's advice, I drafted this learning plan.

Any advice or comments are very welcome! Here is my private email (savinavanderstraten@gmail.com) or feel free to leave a comment directly in the sheet.

I will continuously add suggestions I receive in the second tab of the sheet.

And then, what next?
No, I don't intend to get a job in data science. My plan is to 1) get a high level understanding of data science and machine learning, 2) get involved with startups that use these technologies and have a positive impact on the society (probably on the investment side, but maybe not).

Pretty niche, hm? Yes, this is intentional. As an Associate, I got the chance to see dozens or even hundreds of ideas every month. This is amazing, but has a downside: it is hard to stay focused. Focus in the tech industry is risky as enabling technologies evolve so fast. Having said that, I am confidently betting on machine learning and positive impact for the next few years at least.

Having machine learning capabilities in a product will probably be as basic as being cloud-based in a couple of years. However, understanding how you can get good value from it to solve a specific problem is probably going to stay relevant for ever. As for impact investing, I hope that having a positive impact on society will remain appealing to some people. If not, I am off to Mars!

Thank you
I would like to thank all the amazing people I had the chance to work with during my first VC journey.

First and foremost, I'd like to thank the Point Nine team Christoph Janz and Pawel Chudzinski, who showed me what it really means to be a good VC, Rodrigo Martinez who pushed me many times to become my best and matrixed my mind, Mathias Ockenfels who mentored me with great patience in the early days, Clement Vouillon for his bad jokes and great advice on my blog posts, my fellow truffle pigs Robin Dechant and Louis Coppey and the amaaaazing ops team: Jenny Buch, Karolin Geike, Paula Pastor, Ricarda Friedrich and Aleksandra Zorylo.

Secondly, I want to thank all of the founders I had the chance to work with and share a bit of their great startup adventure including Richard from Juro and Ed from Zype.

Thank you, and I hope to see you very soon!

The article was originally published here

Source: HOB