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September 2, 2021

Meet the Brainbase Team: Nauris Dorbe, Head of Data and Machine Learning

Nauris has been with Brainbase for almost a year now. For most of his career, he has been working on software development. Nauris has worked at Ericsson and Accenture and even co-founded a startup of his own - a forest monitoring platform for forest owners*. 

 

Today, Nauris leads the Data and Machine Learning teams at Brainbase and is, in his own words, “building the future of the IP industry.” He predicts Brainbase will reach the coveted unicorn level in a couple of years. So let’s dig a little deeper and get to know this data wizard.

 

What made you join Brainbase?

It was clear to me during our initial interviews that the company founders are very open-minded and dedicated to building great products. Also, an opportunity to work in a fast-growing startup and make Data and Machine Learning systems from scratch appealed to me. It seems like it is the perfect timing for the right product in a very niche market.

 

How do you think Brainbase is changing the licensing industry?

By making it simple. The licensing business is based on giving another company the right to manufacture and sell your products for a specific payment. This is often an exclusive right and it is important to monitor when a right or contract expires. One must also keep track of detailed sales reports that are often done in Excel. Such activities have a high administrative cost, which is greatly influenced by the time required and the human errors that can occur during data entry and calculation. Brainbase automates this process making licensing simple and efficient. "We also bring all business departments to one place and show them an overview of what is going on in the company. In product development, it is useful to see what is happening on the sales side - which products sell and which do not. It helps you make smarter business decisions and ultimately saves your business time and money.

 

Any upcoming projects you’re excited about?

Democratizing data analysis across Brainbase, giving all users and customers the ability to perform simple analytics without technical knowledge. And developing the Contract Reader - a tool that we will use to onboard clients faster.

 

What does a typical workday look like for you?

A typical workday consists of building Machine Learning and Data solutions, software engineering, and data science. I am committed to helping the team achieve more by maintaining our roadmap, strategy, and context on higher-level company goals. My rhythm: Wake up at 5:30 in the morning, eat breakfast, and work (from home). I then have lunch with my wife and newborn, and I like to take a walk or run outside. After that, I go back to work, spend time with my family and eat dinner until 7 pm (when the baby sleeps). To wrap up the day, I study -  sometimes self-improvement/biography/business books, sometimes I dabble in hobby coding projects, sometimes I take courses to learn a specific technology or idea. I am usually asleep by 10 pm. I’ve been very consistent with this daily plan for the last year. 

 

What motivates you? 

When our solutions are revolutionizing the way users are working in a good way. And positive feedback from our customers about the products we have worked so hard on.

 

What makes you passionate about Brainbase?

I could share many good things about Brainbase, but the single best thing is the people around me and happy customers.

 

Do you have any after-work hobbies/activities? 

I am spending time with my family, reading, and mountain biking. Note - there are no mountains in Estonia but I still find some fun tracks for my skill and experience level. 

 

Last good read or a worthwhile online course you took? 

  1. “Extreme Ownership: How U.S. Navy SEALs Lead and Win” by Jocko Willink, Leif Babin.
  2. “Lying” by Sam Harris.
  3.  

Why would you recommend someone to apply to Brainbase?

  1. Possibility to build things from scratch;
  2. Fast-growing startup;
  3. Great people.

*- The startup consisted of a prototype that analyzed tree species using Sentinel satellite data. Sadly it didn't find the correct business model and paying customers. 

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