Solmaz Shahalizadeh
AI Operating Partner, HGGC. On 1 show, 1 appearance. The Shows tab opens the full record on each.
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Solmaz Shahalizadeh is an AI Operating Partner at HGGC and a Founding Partner at Backbone Angels. She previously spent nine years at Shopify as VP and Head of Data Science & Engineering, where she scaled the data team and developed AI products including Shopify Capital.
1shows
1appearances
16statements
3resolved
2supported
0contradicted
67%fully supported
Everything Solmaz Shahalizadeh said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Causal inference will solve key data problems ignored by machine learning hype
“There's a lot of hype and focus and good work in machine learning. But I do think if we take a step back and look at causal inference, we're gonna actually solve a lot of problems with just that arm. So I hope over the next few years, like, people invest in th…”
Shahalizadeh: Moving from rules to machine learning yields highest lift
“The first time you go from any rule base or non-machine learning to machine learning actually is the time that you get the highest lift.”
Shahalizadeh hires machine learning talent by looking outside traditional ML backgrounds
“I recruit machine learning people by not going after machine learning people.”
Shahalizadeh: Answering simple questions drives more data impact than machine learning
“And I think that's sort of a neglected part of data science. Everyone talks about, like machine learning and building all of these data products, but I think lots of the impact, lots of the trust and usage of data actually comes from being able to answer to so…”
Shahalizadeh: Shopify avoids asking merchants for data without immediate utility
“We don't ask merchants for data that we are not going to give a benefit to them right off the bat.”
Shahalizadeh: Shopify incurred technical debt by jumping straight to ML
“And there has been times that even us, we've sort of, like, jumped to the top top in one of the areas, and you pay the technical debt that you did not do the work in the beginning.”
Shahalizadeh: Shopify ML models are built for individual merchant use cases
“So actually all of our machine learning offerings that I was talking about are actually built for the individual use case of the merchant.”
Shahalizadeh: Shopify supports over 800,000 merchants across 175+ countries
“Last reported number, sort of, is that we are over 800,000 merchants in over a 175 countries.”
Shahalizadeh: Shopify expanded from 300 to over 5,000 employees
“When I joined, we were 300 people, and now we are over 5000, so it's been massive growth, really, over the years.”
Shahalizadeh: Compute advances reduced two-year neural net tasks to one week
“What took me two years along with a team to do, like, right now with the advances over the last few years in compute and in storage, you can do probably over a week.”
Shopify transitioned its ETL platform from Ruby to Python around 2013-2014
“Shopify, the application is still Ruby on Rails, and actually the first version of ETL tooling that was built in house was Ruby, but I think we made this decision of moving to Python around 20 13, 20 14, because we thought it's the language that most of the co…”
Shopify Capital is entirely driven by machine learning
“As of last two years, Shopify Capital is entirely machine learning driven.”
Shahalizadeh: Shopify processes over 600,000 checkouts during peak periods
“At peak time we had over 600,000 checkouts going through”
Shahalizadeh: Shopify admin dashboard home cards are driven by machine learning
“When they log into their Shopify store in the admin, they see a bunch of, like, home cards that tells them do this or, like market for this product or make this change in your theme. And those are all driven by machine learning,”
Shopify shadow-tests machine learning models using Apache Kafka before release
“We run them in shadow mode, which means, like, they do all the evaluation, but the results are logged to Kafka, and we see if the time to response, if the sort of distribution of predictions are different or not.”
One line per show, most statements first. The link opens Solmaz's full record on that show: the calibration, argument clarity, speaking style and every statement made there.
| Show | Role there | Eps | Statements | Record | |
|---|---|---|---|---|---|
 MADLEDGER | AI Operating Partner, HGGC | 1 | 16 | 67% 2/3 | full record on the MAD Podcast → |