Michael Segala. He's the CEO and co-founder of a company called SFL Scientific, a data science consulting firm that specializes in big data solutions. He's for leveraging machine learning in analytics techniques to arrive at insights to numerous industries— from healthcare to stock market predictions. Before founding the company, Michael worked as a data scientist in some of the well-known companies such as Compete Inc., Akamai Technologies and he also holds a PhD in Particle Physics from Brown University.

Famous Five:

Favorite Book? – The Challenger Sale
What CEO do you follow? – Larry Page and Sergey Brin
Favorite online tool? — Slack
How many hours of sleep do you get?— 6
If you could let your 20-year old self, know one thing, what would it be? – "Diversify my education, learn more than just science from the early set, it will help you out"

Time Stamped Show Notes:

01:09 – Nathan introduces Michael to the show
01:56 – The founding members of SFL Scientific are particle physicists
- 02:41 – They have a deeper understanding of the problem—from the academic and business perspective
02:58 – SFL Scientific is completely bootstrapped with $2K as their initial funds
03:07 – SFL Scientific got their first client only a few weeks after their launch
03:24 – The first client was a group of people from Stanford studying sleep apnea
- 03:30 – Sleep apnea is a disease that makes you stop breathing for a couple of minutes while sleeping and can lead to death
- 03:46 – The group's idea is to take the sound and record it through an iPhone app at night
- 03:59 – The group hired SFL Scientific to build an entire suite of AI machine-learning product solution
- 04:04 – SFL Scientific also got an FDA resolution for the product
04:30 – SFL Scientific is a complete professional-based consulting firm
- 04:40 – They write specific algorithms for the clients depending on their needs
05:18 – SFL Scientific got their first client in 2015
05:24 – Michael is now 31
05:44 – The pricing depends
- 06:17 – For a high-level R&D-based projects, the charge is hourly
06:34 – SFL Scientific does R&D-based projects with minimum requirements
07:10 – Most clients don't understand the scope of the project so SFL Scientific asks business questions or strategy
- 07:45 – SFL Scientific provides the possible end result
08:08 – First year revenue is low 6 figures
08:27 – SFL Scientific has 3 co-founders
- 08:38 – Michael does more on the sales stuff such as talking with client, one handles the technical and the other handles the implementation of behind-the-scenes coding
- 09:14 – Equity is almost equal with Michael getting 34%
- 09:37 – The first 2 years, they invested back into the company most of what they got
- 09:53 – They had some very low salaries
10:27 – SFL Scientific almost broke a million in 2016
10:42 – 2017 revenue might go over and above a million
10:57 – Team size is 10
11:30 – SFL Scientific currently has a dozen clients
11:38 – One of the clients takes up around 20% of the revenue and Michael knows that it is dangerous
12:00 – SFL Scientific has no churn yet
12:08 – SFL Scientific mitigates a couple of ways the employees can work on multiple projects at a time
12:24 – SFL Scientific doesn't invest only in one problem—go vertical to diversify the risks
13:12 – Looking at data science in general, the challenges are unanimous
13:34 – SFL Scientific is capable of understanding and solving cases from different industries
14:07 – Nathan just finished Thinking in Systems
15:48 – If you don't have decent data to support a model that is accurate to a certain degree, you're not going to get anywhere
17:03 – SFL Scientific looks at the potential of a project
17:16 – Michael is most excited with the health industry in terms of AI and machine learning
19:15 – The Famous Five

3 Key Points:

Consider yourself lucky when you're completely bootstrapped and you end up getting your first client only after a few weeks of launching.
It's quite risky to only solve one problem as a company; diversify your services so you have a greater chance of surviving.
Study different fields and see how you can solve cases from these different industries.

Resources Mentioned:

The Top Inbox – The site Nathan uses to schedule emails to be sent later, set reminders in inbox, track opens, and follow-up with email sequences
Klipfolio – Track your business performance across all departments for FREE
Hotjar – Nathan uses Hotjar to track what you're doing on this site. He gets a video of each user visit like where they clicked and scrolled to make the site a better experience
Acuity Scheduling – Nathan uses Acuity to schedule his podcast interviews and appointments
Host Gator– The site Nathan uses to buy his domain names and hosting for the cheapest price possible
Audible– Nathan uses Audible when he's driving from Austin to San Antonio (1.5-hour drive) to listen to audio books
Show Notes provided by Mallard Creatives

S2E48: L'héritier de Bauto