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What's the Impact?
Causal Research for Marketing, Product, and Data Science Partners
Interview and Career Coaching
Jonathan is a senior data scientist at Airbnb. The last time Jonathan was on the job market, he went 9 of 10 for technical round case-study and take-home challenge interviews with invitations to the final round. He then went 7 for 7 within a 2-week period before withdrawing for the last two. These companies included Stripe, Meta, Amazon, Uber, fka Twitter, Robinhood, and more. Most recently, Jonathan has passed Staff DS technical rounds at Netflix and Meta before pausing his candidacy to travel the world.
While at Airbnb, Jonathan has expanded his career coaching business with the most popular request being for case-study mock interview support, with clients receiving offers from Junior to Senior to Staff at companies including Meta, AirBnb (2x), Uber (3x), Google (2x), TikTok, Snapchat, Discord, Etsy, BCG, and more.
Jonathan has also done coaching outside of interview prep including resume reviews, advice transitioning into data science, networking, and tutorials related to experimentation, statistics, and observational causal inference. See more: COACHING SERVICES
Data Science Interview Course
After two years of coaching data scientists to offers at Meta, Google, Uber, Airbnb, Stripe, TikTok, Discord, and more — junior through staff levels — I've packaged the core framework into a course.
The Data Science Case Study Framework covers exactly what I walk clients through before mock interviews: how to systematically approach any experimentation or causal inference case study, regardless of industry or team. 85 minutes, 6 videos, applicable from junior through staff levels.
Order Here: Data Science Interview Course: Master the Case Study
Jonathan Hershaff, PhD
Jonathan Hershaff is a Data Scientist and Economist with a PhD from the University of Michigan. He has more than a decade of experience in causal modeling, having worked at Airbnb, Stripe, Collage.com (sold e-commerce startup), the Securities and Exchange Commission (SEC), the Federal Reserve (DC), and Wells Fargo Bank.
Dr. Hershaff had research cited in a winning US Supreme Court Case, has testified as an expert economic witness teaching a Grand Jury about investor advisor fraud, published in peer-reviewed journals, and presented at multiple economics and public policy conferences.
While in the tech sector, Dr. Hershaff worked closely with both C-suite executives and senior leadership across marketing, sales, product, and engineering. He also has extensive experience partnering with SEC and DOJ attorneys.
Why Causal Research?
Sales have increased following a new marketing campaign. Conversion rates have fallen after a feature launch or website change. Were these due to the team's changes or external factors out of our control?
Example: Return on ad spend (ROAS) for branded search looks great at a glance, but how many of those conversions would have gone through organic SEO links if paid ads weren't there?
Example: We're considering investing in insurance against a bad outcome for our users, but not sure how much our customers would penalize us if that bad outcome occurs. We certainly don't want to experiment with negative experiences; how do we find the cost of such events?
Causal research can help to answer these difficult questions, even when experimentation is not a viable option and we are left with only observational data. Results can inform marketing budgets, product decisions, headcount, and more.
Request a consultation
Schedule a risk-free, no-obligation, no-sales-pitch call today to discuss your research needs, and whether this partnership is a strong fit.