The Data Scientist Show - Daliana Liu

A/B testing and growth analytics at Airbnb, building data science tools and metrics store with Nick Handel, the data scientist show#037

May 24, 2022

02:10:07

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Highlights

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Episode notes

Machine Learning

01:45

Data Science - How to Avoid Random Hypotheses That Are Meaningless?

01:36

Is There a Future for Data Science Tools?

04:46

Introduction

3min

What's the Day to Day Like as a Data Analyst in Black Rock?

3min

How Did You Get to AirBeand Be?

3min

Data Science Tools, the Experimentation Framework?

3min

What Are Common Mistakes People Make With Product Experiments?

3min

Cannibalization

2min

The Power of Product Experiments

2min

Is the Unit of Experimentation Standardized?

2min

Do We Really Need to Log People Out After 40 Hours?

4min

10.

Is There a Framework for Data Science?

3min

11.

Data Science - How to Avoid Random Hypotheses That Are Meaningless?

2min

12.

How to Build Trust in the Data Science Industry

5min

13.

Yen, You Don't Read It All.

2min

14.

Logging Experiments Are Impacting Customer Service Tickets

3min

15.

Do You Coordinate?

2min

16.

The Biggest Surprising Thing About Ab Testing?

4min

17.

Is There a Good Culture of Experimentation?

2min

18.

You'll Learn Something From It

5min

19.

Using Event Logging to Analyze Data

4min

20.

Machine Learning at Arbanby - What's the Story?

3min

21.

Machine Learning and Events - A Great Case Study

4min

22.

Machine Learning Models - How Do You Know if You're Not Missing Something?

6min

23.

Arn Beand B - How to Scale for Different Use Cases

2min

24.

Using Python in Machine Learning Models?

1min

25.

Building Tooling Is Really Hard, Is It?

2min

26.

Scaling a Business

2min

27.

Build a Tool - What Are Some Other Important Decisions You Made?

2min

28.

Machine Learning - What's the Future Store?

3min

29.

A Data Scientist's Perspective on Machine Learning and Machine Learning

2min

30.

Data Engineering - The Hard Part Was Generalization, Right?

5min

31.

Transform Is a Metric That Is the Language for Data.

2min

32.

Using a Semantic Layer for Machine Learning?

3min

33.

Are You Building a Reporting Tool?

4min

34.

Is There a Future for Data Science Tools?

5min

35.

Machine Learning

2min

36.

Metric Flow

3min

37.

Is It Really Important to Generate Metrics for Product Experiments?

3min

38.

What Are Some of the Lessons You Learned From Data Science?

4min

39.

Don't Follow the Formula, Do Sandwich?

3min

40.

Are You Making These Mistakes as a Data Scientist?

3min

41.

The One Example of the Industry Is Missing

2min

42.

What Do You Learn From Your Brother?

2min

43.

I've Learned a Lot From My Co-Fender

3min

44.

Are You Planning a Wedding Already?

3min

Nick Handel was a senior data scientist leading the launch of the data side of this Airbnb Trips and later built a team that designed aribnb’s end-to-end machine learning platform, bighead. Currently, he is the cofounder and CEO of Transform, he first centralized 'metrics store' that empowers data analysts to deliver insights. He was recognized as 30 under 30 by Forbes in 2018. If you like the show subscribe to the channel and give us a 5-star review. Subscribe to Daliana's newsletter on www.dalianaliu.com/ for more on data science.

Daliana's LinkedIn: https://www.linkedin.com/in/dalianaliu/

Daliana's Twitter: https://twitter.com/DalianaLiu

Nick's Linkedin:https://www.linkedin.com/in/nicholashandel/

Highlights:

(00:00) intro and career journey

(00:10:58) common mistakes in A/B testing

(00:25:48) how to do A/B testing deep dives

(00:27:32) surprising A/B testing results

(00:29:18) facts vs opinions

(00:33:55) A/B testing best practices

(00:55:01) how he built a new data schema for Airbnb Trips

(01:00:43) how to collect data when building data science tools

(01:38:53) trend of data science tools

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