How To Do Proper Crypto Research with Covalent Senior Data Scientist Brandon Rochon

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Below is a $GCR Exclusive interview with Brandon Rochon, senior data scientist at Covalent. We dive into how to generate Alpha insights using the Covalent API.

Question: Hi Brandon! Can you share a bit about your background and how you became senior data scientist at Covalent?

I have a background in Mechanical Engineering and Finance with a strong itch for innovation and entrepreneurship. After co-founding and failing an energy analytics startup I found myself enthralled with data science. One thing led to another and I ended up as a Research Assistant at the University of Calgary doing academic research on DeFi. The best place to get the data that we needed for research was Covalent so I was using the API all of the time and it just made sense to join the team from there.

What attracted you to Covalent?

The product was my first landing point and it was solid. Once I met the team, the decision was easy. Ganesh leads a relentless team with a focus on shipping value adding products. Everything we do is to add value in some way and that makes it both fun and fulfilling. 

Tell us more about Alpha Alarm and the Alchemists program.

The two are separate initiatives at Covalent. Alpha Alarm exists to flex the Covalent API and ship daily DeFi visuals/insights. It is run by myself and a strong team of Alchemists. That brings me to the Alchemist program – which is masterfully organized by Jackie. It is a 2000 person (and ever-growing) ambassador program that has the same focus on shipping value. They have been responsible for spearheading 27 regional communities (27 different languages) as well as a translation publication into 23 different languages. 100+ Alchemists have stepped into leadership positions and are now running their own teams. Many are even starting to recruit for their teams on LinkedIn and other job sites.

Can you share some key alpha from Alpha Alarm? 🙂

After generating 100+ charts and doing daily research over the last 2 months, I am yet to find the limit of Covalent’s API/DB. The data is all there, if you want it you can have it. Data powers decision making and as DeFi grows data will be more and more important. The key alpha, regardless of how you do it, is to watch the data and do your own research. It isn’t hard to do and it is an extremely valuable habit to build.

GCR x Covalent Media Mining is in full speed right now- can you share some best practices on how researchers and analysts should be using Covalent to generate ideas for their research or insights? Where are the best resources?

I think the best advice I can give is to follow down something that YOU are interested in. The research process will take time and it’s tough to get through it if you need to force your way through it. Beyond that, you should check out the examples on www.covalenthq.com/docs. There is also a topic calculator that is very useful to find different log events. Also, Etherscan and excel make for a great prototype. Just come up with a theory and do a quick verification with Etherscan and/or excel. Then dig deep after that. 

What are some common mistakes made by researchers and analysts when using Covalent in doing research?

I think the most common mistake is to try and scale a theory/question too fast. The Covalent API has a great CSV feature and you can filter by block height or date. Start with a day worth of data and work with that in excel. Once you get past that, you can very easily scale it up to a live dashboard or a larger CSV call if that is preferred. Either way, start small, use the filters, and keep it manageable – then think big and dig deep once you have a prototype.

What kind of research pieces would you like to see more of in the crypto space? What’s your advice for researchers when writing a piece for the broader crypto market?

It would be great to see more discussion and critical thoughts inside research in crypto. Take a critical position of your theory and disprove it rather than taking a supportive position and proving that. Or do both. Point is, research should be about analyzing raw data and following whatever it says. When you are your own devil’s advocate, it improves your research and your thinking.

Any undercovered areas that you think are super interesting?

Options. I am a finance guy by training and I think crypto options will be huge moving forwards. Unfortunately, the decentralized crypto options are pretty thin and scarce – they exist but the choices are just not there yet. I think some solid research and innovation can help push this forward.

What are some secret or lesser known Covalent product features or addons that folks can be using?

The tools at www.covalenthq.com/docs are underutilized and we are working to change that. There are a ton of features and learning materials there that should act as a jumping off point before diving into the API.

Lastly, what’s your advice for folks to be more data conscious in crypto? How can we be more rigorous in our thinking?

Similar to my answer above, I think everyone needs to be more critical in crypto. There is a ton of hype (and there should be) but it needs to be balanced with some individual critical thinking. Spend some time in your own head and think about things opposite to what your default is. I think crypto is the way forward but that doesn’t mean it is perfect, the best way to find improvements is through critical thinking in research.

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