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Jeremy Stanley

Co-Founder & Chief Scientist, Anomalo · 1 appearance on the record.

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founderscientistexecutiveauthor@jeremystan ↗LinkedIn ↗anomalo.com ↗

Jeremy Stanley co-founded Anomalo, an enterprise AI platform for automated data quality monitoring, after previously serving as VP of Data Science at Instacart. He is also the co-author of the O'Reilly book Automating Data Quality.

12statements → 8claims → 1claims resolved → 4.17/5average certainty → 1.58/5average debate potential →

0 supported 0 partly supported 1 contradicted 7 not checkable as stated how the 8 claims stand · each chip opens the sources

1 prediction · 7 assertions · 2 insights · 2 disclosures · every statement was checked. The prediction and assertions are the 8 claims: statements the public record can support or contradict. 1 is resolved, and 7 name no date, number or outcome precise enough to check. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.

The record, in short

What the tape says about how Jeremy argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

Their most notable contradicted claim

Prediction Didn’t hold up
Instacart projects reaching profitability and positive cash flow by late 2017
“And in the next 12 months, we're gonna be a profitable company, cash flow positive.”
Jeremy Stanley Sep 30, 2016 ▶ 4:50 Making On-Demand Delivery Profitable // Jeremy Stanley, Instacart (Data Driven NYC / FirstMark)

How they sound: speaking style how? →

248 words/min while actually speaking · 29.6 um and uh per 1k words

No argument clarity score for Jeremy Stanley: no usable question→answer exchanges on raw tape (a fair score needs 8+). We do not score a sample that small. Roundtable and news formats yield far fewer direct exchanges than interviews.

Measured by listening to the audio itself: 3,914 words across 1 episode of raw-level tape, transcribed verbatim with every um and uh kept, each one attributed only where the alignment onto our timed stream is unambiguous. These are measurements of speaking style. We do not rank them: across this corpus, fluency and argument quality are nearly uncorrelated (ρ≈0.2), and smooth talking does not signal clear thinking. How it's measured →

Everything Jeremy Stanley said on the MAD Podcast that made the record, most notable first. Filter by type, assessment or year in the ledger →

Prediction Didn’t hold up
Instacart projects reaching profitability and positive cash flow by late 2017
“And in the next 12 months, we're gonna be a profitable company, cash flow positive.”
Jeremy Stanley Sep 30, 2016 ▶ 4:50 Making On-Demand Delivery Profitable // Jeremy Stanley, Instacart (Data Driven NYC / FirstMark)
Insight
Startups should not hire data scientists before reaching an MVP
“Basically my advice is not to start a startup with a data scientist. You know, focus on getting to MVP, getting some traction, generating some real data, make good decisions early on, and then hire data scientists as you scale.”
Jeremy Stanley Sep 30, 2016 ▶ 22:26 Making On-Demand Delivery Profitable // Jeremy Stanley, Instacart (Data Driven NYC / FirstMark)
Assertion Not checkable as stated
Instacart achieved profitable unit economics in summer 2016
“We've achieved profitable unit economics, it happened in the summer”
Jeremy Stanley Sep 30, 2016 ▶ 4:17 Making On-Demand Delivery Profitable // Jeremy Stanley, Instacart (Data Driven NYC / FirstMark)
Assertion Not checkable as stated
Instacart's routing models predict Manhattan travel times twice as well as Google
“If you just take the predictions out of Google Maps API, you'll be able to explain about 25% of the variance. If you look at the models that we built internally that use a lot more of our historical data, we can get up to about 50% of the variance explained.”
Jeremy Stanley Sep 30, 2016 ▶ 10:20 Making On-Demand Delivery Profitable // Jeremy Stanley, Instacart (Data Driven NYC / FirstMark)
Assertion Not checkable as stated
Instacart grew revenue by 500 percent between early 2015 and late 2016
“Since the beginning of last year, we've grown revenue 500%.”
Jeremy Stanley Sep 30, 2016 ▶ 4:39 Making On-Demand Delivery Profitable // Jeremy Stanley, Instacart (Data Driven NYC / FirstMark)
Insight
Unifying objectives into one function beats coarse optimization constraints
“Oftentimes you start out with a system like this, and because it's such a huge space to explore, you put in a lot of really coarse constraints up front. You know, don't do this if x, right? Most of those constraints are reasonable, but bad 10% of the time, and…”
Jeremy Stanley Sep 30, 2016 ▶ 13:30 Making On-Demand Delivery Profitable // Jeremy Stanley, Instacart (Data Driven NYC / FirstMark)
Assertion Not checkable as stated
Ninety percent of Instacart customers are repeat buyers
“90% of our customers are repeat customers.”
Jeremy Stanley Sep 30, 2016 ▶ 4:48 Making On-Demand Delivery Profitable // Jeremy Stanley, Instacart (Data Driven NYC / FirstMark)
Assertion Not checkable as stated
Instacart's repeat customers spend around $500 per month
“They spend about 500 dollars a month with us”
Jeremy Stanley Sep 30, 2016 ▶ 4:50 Making On-Demand Delivery Profitable // Jeremy Stanley, Instacart (Data Driven NYC / FirstMark)
Disclosure
Instacart tests delivery discounts to incentivize demand during off-peak capacity
“Ah, and we're increasingly testing, ah, reversing it, and actually giving discounts when we have a lot of capacity to try to incentivize demand to times when we have lots of shoppers available.”
Jeremy Stanley Sep 30, 2016 ▶ 9:10 Making On-Demand Delivery Profitable // Jeremy Stanley, Instacart (Data Driven NYC / FirstMark)
Disclosure
Instacart recomputes routing plans every minute in every market
“We recompute our plans every minute in every one of our markets”
Jeremy Stanley Sep 30, 2016 ▶ 13:21 Making On-Demand Delivery Profitable // Jeremy Stanley, Instacart (Data Driven NYC / FirstMark)
Assertion Not checkable as stated
Instacart's 100-person engineering team includes 25 data professionals
“Engineering is around say a hundred people. Out of that there's about 25 that are data related. About five are data engineering. About 10 are analytics, which is really decision science, helping to inform the decisions that the product managers or operations t…”
Jeremy Stanley Sep 30, 2016 ▶ 14:51 Making On-Demand Delivery Profitable // Jeremy Stanley, Instacart (Data Driven NYC / FirstMark)
Assertion Not checkable as stated
Instacart's data stack relies on Postgres, AWS Redshift, Python, and R
“All of our production data is in Postgres, and we will read from the secondaries in AWS. We push all of the Postgres data into Redshift and do a lot of more intensive batch computations off of Redshift. The data science teams are using either Python or R we do…”
Jeremy Stanley Sep 30, 2016 ▶ 17:10 Making On-Demand Delivery Profitable // Jeremy Stanley, Instacart (Data Driven NYC / FirstMark)

Appearances (1)

EpisodeDateSpeaking time
Making On-Demand Delivery Profitable // Jeremy Stanley, Instacart (Data Driven NYC / First Sep 30, 2016 17m
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