“In Conversation” Series

Data Science at Massive Scale: In Conversation with Solmaz Shahalizadeh, Shopify

Shopify (NYSE:SHOP) is one of those unlikely success stories that entrepreneurial dreams are made of.

In 2006, co-founder and CEO Tobias Lutke was a 24 year old German autodidact programmer who had followed his girlfriend to Ottawa, Canada. He partnered with an older entrepreneur, Scott Lake, to start an eCommerce business selling snowboards, Snowdevil. As Tobi realized there was no decent out of the box framework to build an e-commerce store at the time, he started building the Daredevil snowboard store from scratch, using the then nascent Ruby on Rails. Word spread out within the community about the quality of his work, and the duo decided to focus on the software platform, rather than the snowboard store. A world away from Silicon Valley, Shopify was born.

Fast forward to today , with many steps along the way, including a Series A round of financing in which our firm FirstMark invested: Shopify is a ~$34B public company that’s grown extremely fast in recent years and helps SMBs outfit their stores with a variety of essential tools. Shopify powers the online stores of more than 800,000 merchants in over 175 countries.

As tends to be the case for all major Internet franchises, Shopify recognized early the transformational power of harnessing and using data. Data science and machine learning were used in one product, then the next and over the years have become a cornerstone of the company.

The Path to a $2.7B Unicorn: In Conversation with Zach Perret, CEO, Plaid

“We are, by far, the earliest company here”. This how Zach Perret, CEO of Plaid, started his talk at his first appearance at Data Driven NYC, back in February 2013. “We are basically three guys, coding 24 hours a day, and building developer tools…”.

Fast forward to today: the company was valued at $2.7B (“allegedly”, says Zach) in its most recent $250M round; Plaid has integrated with 15,000 banks in the U.S. and Canada and 4,000 fintech applications. One in four people in the U.S. have linked an account using Plaid. And they have just acquired New York based competitor Quovo for $200M (“reportedly” as well).

Not bad for a self-described “data plumbing” company. As today’s consumers expect to live fully digital financial lives, with their phone at the core, Plaid provides the financial infrastructure that enables developers in fintech companies to build great applications, and have consumers connect those to their bank accounts – basically Plaid is the connective tissue between the app and the bank, and takes care of moving all the data back and forth in the background.

It was a lot of fun having Zach back at the event 6 years later. Here’s the video of our fireside chat, and my notes are below the fold.

Go to Market Strategies for Enterprise Startups: In Conversation with Martin Casado, GP, Andreessen Horowitz

What is the number one mistake technical founders make? Why is pricing so important? Should entrepreneurs avoid at all costs having a service component to their business? What is fundamentally new and different in go to market strategies for modern enterprise software startups?

A self-avowed “failed physicist”, Martin Casado is a General Partner at Andreessen Horowitz, and previously was the co-founder and CTO of Nicira, a pioneer in software-defined networking and network virtualization that was acquired by VMware for $1.26 billion.

I have had the pleasure of getting to know Martin through the board of ActionIQ, a great NYC startup in which we are both investors.

Martin joined us for a fireside chat at the most recent edition of Data Driven NYC. The conversation centered largely around one of Martin’s favorite topics, go to market strategies for enterprise startups. There’s plenty of interesting thoughts and directly applicable advice for entrepreneurs in there, as Martin spoke as much from his previous founder experience as he did as a VC.

Here’s the video, and my notes from the chat are below the fold.

From 0 to $200M in Revenues in 7 years: In Conversation with Ben Uretsky, Co-Founder, Digital Ocean

Who would be crazy enough to compete head-on with AWS?

The question was almost as obvious seven years ago than it is today. Yet in just a few years since its founding, Digital Ocean, a cloud infrastructure startup based in New York with data centers around the world, has managed to build a very impressive and fast-growing business, successfully competing with the giants of cloud computing.

Ben Uretsky, co-founder of the company (with his brother Moisey and 3 others) and its CEO from 2011 to 2018, stopped by for a chat at Data Driven NYC to tell the story of the company and share some lessons learned.

Here’s the video, and below are my notes from our great chat.

Continue reading “From 0 to $200M in Revenues in 7 years: In Conversation with Ben Uretsky, Co-Founder, Digital Ocean”

Data, AI & Hedge Funds: In Conversation with Matt Ober, Chief Data Scientist at Third Point

The hedge fund world has been evolving dramatically over the last few years.

Just like in other industries, software, data and AI/ML have been playing an increasingly important, and disruptive, role. Many hedge funds have been scrambling to embrace this evolution – not just to gain an edge, but also to avoid becoming extinct.

Certainly, quantitative hedge funds have been making heavy use of software and data for a while now. The “quant” funds rely upon algorithmic or systematic strategies for their trades – meaning that they generally employ automated trading rules rather than discretionary (human) ones, and they will trade tens or hundreds of assets simultaneously.

But another big part of the industry, the “fundamental” hedge funds, had been operating very differently. Those funds will perform a bottoms up analysis on individual securities to value them in the marketplace and assess whether they are “undervalued” and “overvalued” assets. They’ll often have a much more concentrated portfolio.

In part because the entire hedge fund industry has been performing generally poorly recently (years of performance trailing the stock market), there’s been mounting pressure on hedge funds to evolve rapidly, particularly fundamental ones.

A couple of years ago, Third Point made a big splash when they hired Matt Ober, who was 32 at the time, to become their Chief Data Scientist. Dan Loeb, the billionaire founder of Third Point, was a prime example of a fund manager who had reached tremendous success through a fundamental approach. His efforts to hire Matt away from his previous employer and make him Third Point’s head quant was widely viewed as a sign of the times. Continue reading “Data, AI & Hedge Funds: In Conversation with Matt Ober, Chief Data Scientist at Third Point”