Employee Spotlight #27: Andrei Lyskov, Former Data Scientist At Apple & Coinbase

Andrei Lyskov is an ex-Apple & Coinbase data scientist, now CEO of a stealh generative AI company focused on the creative economy and helping creators monetize. He’s also published a best-selling book called The AI Sages (www.theaisages.com), and has been published or quoted in the Wall Street Journal, Forbes, Huffington Post, and Startup Grind.

Frederick Daso: What was your journey to becoming a data scientist at Coinbase and Apple and now the founder of your new startup?

Andrei Lyskov: I started working at age ten, delivering newspapers, and at 12, I realized I could make a lot more money writing botting scripts for Runescape and selling digital gold on the black market. 

This started my lifelong obsession with computers and programming. Growing up and attending college in Canada, it was quite clear that if I wanted to have any impact in tech, I would need to move to California. So I did a bunch of internships and spent extensive time there. I worked for a lot of great companies like Soylent and Peerstreet before landing at Apple after graduation.

It certainly wasn’t a linear path; at one point, I switched from my Canadian university to Make School, an alternative college program in SF, before dropping out of that to work at Soylent. Landing my first data science job at Apple was also a big grind, and I wouldn’t have even gotten an interview if it wasn’t for a great mentor of mine, Manuel Arora vouching for me. 

Once I got my foot in the door, I skipped classes for two weeks in preparation for the interview and got the job which was great validation after years of hustling to break into big tech. I’ve also been into crypto since 2014 (missed the ETH ICO, unfortunately), so when Coinbase recruiter reached out, I figured it was a good time to switch things up. 

However, a year in, I saw Stable Diffusion’s impact on the world and knew this would be bigger than the internet. When chatGPT came out, that solidified my conviction. After writing a book in a day using these tools (www.theaisages.com), I was successfully AI-pilled and realized it was time to start a company instead of watching from the sidelines.

Daso: There’s a lot of conventional career advice about being a successful data scientist, but are there any unorthodox lessons you’ve learned through experience or been taught through mentorship that more of your fellow data scientists should know?

Lyskov: “Why should I care?”

This was the scathing feedback I received after delivering one of my first presentations to a stakeholder at Apple. I had painstakingly conducted a very intricate statistical analysis and made a beautiful presentation, only to be completely shot down. 

And they were right! I did an academic project with no business value. From that day on, I’ve always been guided by this question - why should they care? Driving all my analysis and machine learning projects to deliver some tangible outcome (typically increasing revenue or reducing costs)

Daso: What’s the toughest project (professionally or personally) that you worked on as a data scientist or in general? What were the most important lessons you learned from that project?

Lyskov: One of the most challenging projects I undertook was to develop a machine learning model for predicting viewership trends at Apple. Specifically, I was tasked with creating a model that could accurately predict which subscribers would still be using our newly launched product, Apple TV+, three months after signing up.

This project was particularly complex due to several factors, including the fact that Apple was offering a one-year free hardware bundle and a seven-day trial to all new subscribers. Rather than building two separate systems, my team and I created a single model that used the first three days of user activity to predict longer-term viewing habits.

By doing so, we were able to allocate our advertising spend better, focusing on partners who were delivering high-value users within the first three days of their subscription. This approach proved extremely successful and helped us to identify fraudulent channels and optimize our ad spend, saving Apple millions of dollars in the process.

Throughout the project, I learned much about project management and collaboration, working closely with data engineers, business managers, and advertising executives to ensure the model’s success. Overall, the experience taught me the importance of pacing a project effectively and engaging with diverse stakeholders to achieve a common goal.

Daso: Who are some of the most inspirational people you’ve gotten to work with during your career in tech? 

Lyskov: My old director at Apple, Ayman Khalil, was awesome to work with. Despite running a giant organization of over 150 people, he always made time to check in and talk about my career and how he could help push along certain projects. Unlike other data science leaders I’ve encountered, he’s able to perfectly straddle the technical and non-technical worlds, with an eye for delivering real business value vs. spending time on frivolous vanity data science projects that don’t lead anywhere.

The other person is Karthik Ganapathi, my original manager at Coinbase and helped shape my understanding of Crypto. Like Ayman, he’s able to dive into the weeds and get technical while also stepping back and asking, “What’s the point?” During the tumultuous time that Coinbase went through with several re-orgs and layoffs, he was a great calming presence to help keep the ship steady.

Daso: How would you define your company’s culture, and how does it create an environment where you can do your best work?

Lyskov: I currently hold the position of CEO at an innovative generative AI company that operates in stealth mode, with a specific focus on empowering creators and compensating them for their work.

At our company, we value and prioritize three key principles that define our culture:

Learners: We strive to surround ourselves with individuals deeply committed to lifelong learning. This is why I initiated Nerd Night, a community in LA aimed at nurturing intellectual curiosity and a willingness to expand one’s knowledge base. It is disheartening to hear individuals admit they have not engaged in any new learning since college. The speed of AI development means that the ability to learn quickly and effectively is a fundamental requirement for success in our organization.

Earners: For a business to thrive, it must generate revenue. We understand that the lifeblood of our company is profit while also acknowledging the importance of integrating conscious capitalism into our business model. Therefore, we conduct extensive background checks on potential investors and employees, specifically screening for any affiliation with the Chinese Communist Party. We take a principled stance on accepting investment, as there are other untainted or less tainted sources of capital available. We have no interest in operating in China or funding any gain-of-function research there ;-).

Burners: We draw inspiration from Burning Man, an annual event celebrating community, art, self-expression, and self-reliance in the Nevada desert. Our company embraces the ten core principles of Burning Man, with Radical Self-Reliance and Communal Effort being particularly important values that contribute to the success of any business.

Daso: What are the most important skills you’ve had to develop in your job, and what specific projects or assignments did you work on to develop each core skill?

Lyskov: One of the most crucial skills to cultivate is emotional intelligence (EQ) and intuition. While it may not be something that can be taught outright, it is certainly an ability that can be enhanced over time. Many resources, such as the timeless classic “How To Win Friends and Influence People,” exist to aid in this pursuit.

In today’s high-IQ industries like data science and machine learning, those with strong EQ and the ability to connect with colleagues and customers often excel. Nobody wants to collaborate with a brilliant but insensitive person who only thinks about themselves. Unfortunately, our society glorifies individualism to an extreme degree, disregarding the reality that we are all part of a larger whole and no one can succeed alone. As John Donne said, “No Man Is An Island.”

Daso: What’s one interesting thing (non-work related) that more people should know about you?

Lyskov: I wrote and published a best-selling Amazon book in a day using ChatGPT and Stable Diffusion. You can grab a copy on Amazon and learn more at www.theaisages.com

Daso: What’s something you want to accomplish in your career that you haven’t yet? What motivates you to get there?

Lyskov: In Greek mythology, Prometheus was a titan who stole fire from the gods and gave it to humanity, defying the divine order. As a CEO of an AI company today, the myth of Prometheus can be seen as a symbol of innovation and disruption.

Like Prometheus, AI CEOs often break new ground and challenge established norms, pushing the boundaries of what is possible with technology.

However, the story of Prometheus also serves as a warning against overreaching and facing the consequences of going too far too fast.

As AI advances at an unprecedented pace, CEOs must balance their ambitions with responsible decision-making and ethical considerations to avoid potential risks and unintended consequences.