Jake Klamka

Angel Investor · 1 appearance on the record.

computed by AI from the episodes · how this works → · full disclaimer →

founderinvestorexecutive@jakeklamka ↗insightdatascience.com ↗

Jake Klamka founded Insight Data Science, a fellowship program that trained thousands of PhDs and engineers to transition into industry data science and machine learning roles. He is also an active angel investor in technology, education, and AI startups.

5statements → 1claims → 1claims resolved → 3.8/5average certainty → 2.2/5average debate potential →

0 supported 1 partly supported 0 contradicted how the 1 claim stands · each chip opens the sources

1 assertion · 4 insights · every statement was checked. The predictions and assertion are the 1 claim: statements the public record can support or contradict. 1 is resolved. 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 Jake argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

How they sound: speaking style how? →

289 words/min while actually speaking · 38 um and uh per 1k words

No argument clarity score for Jake Klamka: only 1 usable question→answer exchange 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: 4,549 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 →

What they said5 Episodes1

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

Insight

The biggest mistake companies make is interviewing data scientists like software engineers

“Great question. And so, again, this is biased predominantly towards sort of tech companies, but I think the biggest one is actually interviewing them as if they were software engineers. And so, in particular, the fellows, when they graduate, the program go int…”

Jake Klamka Mar 20, 2014 ▶ 21:58 Jake Klamka, Insight Data Science // Data Driven #25 (Hosted by FirstMark Capital)

Insight

PhDs outperform master's graduates in data science because of research experience

“From what I've seen, yes. And I'm, clearly I'm biased, because I'm working with a bunch of PhDs, but I've also, but in speaking with a lot of hiring managers, the answer I've heard is yes. And the reason is the, that underlying skill set of, in data science, y…”

Jake Klamka Mar 20, 2014 ▶ 19:01 Jake Klamka, Insight Data Science // Data Driven #25 (Hosted by FirstMark Capital)

Insight

Industry data scientists must aim for 80% perfection, unlike in academia

“Your goal is to go get everything a hundred percent right and then publish, and if that takes a couple of years, then you take a couple years. Ah, in our industry, in, you know, in industry, clearly that's not gonna work. Ah, you wanna probably get to, like, 8…”

Jake Klamka Mar 20, 2014 ▶ 15:22 Jake Klamka, Insight Data Science // Data Driven #25 (Hosted by FirstMark Capital)

Insight

Test data science candidates on learning velocity instead of static skills

“Adjust your, if at all possible, try to think of ways to adjust your hiring process to test for how quickly they're able to kind of traverse this gap. Kind of get two data points basically and see how, how quickly they're moving along instead of just kind of t…”

Jake Klamka Mar 20, 2014 ▶ 16:47 Jake Klamka, Insight Data Science // Data Driven #25 (Hosted by FirstMark Capital)

Assertion Partly supported

Klamka: PhD graduates increase while academic faculty positions stay flat

“The amount of PhDs, granted, keeps going up, but the amount of faculty positions has been flat.”

Jake Klamka Mar 20, 2014 ▶ 3:51 Jake Klamka, Insight Data Science // Data Driven #25 (Hosted by FirstMark Capital)

Appearances (1)

Episode	Date	Speaking time
Jake Klamka, Insight Data Science // Data Driven #25 (Hosted by FirstMark Capital)	Mar 20, 2014	19m

Jake Klamka

The record, in short

How they sound: speaking style how? →

Appearances (1)

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