Hi, I’m Jeff!

10 second bio

I’m a Senior Data Scientist at Netflix, focusing on ads forecasting & optimization. I’ve spent the last eight years building ML systems for Netflix, Doordash and Spotify.

I’ve built GenAI products. I helped build the initial versions of yourmove.ai, an AI dating assistant, scaling it to over 10k users.

I’m an educator. I wrote courses on ML Process, ML Algo’s, ML Business Course used by more than 10k students. I’ve also coached 50+ people in data science interview prep.

If you need help building ML systems, ML hiring or career coaching, shoot me a note: dj.jeffmli@gmail.com

Best Articles

To help you find something that interests you, I’ve curated my best content:

I got 7 job offers during the worst job market in history. Here’s the data...... I tracked every interview, application I sent for my last three job searches. Some analysis on how I got 7 offers.

How Three Tech Dudes Biked 500 Miles from SF to LA: A few friends and I decided to bike from San Francisco to LA. 500 miles. Over 20,000 feet of elevation. A knee injury, 12 flat tires, one person stranded. Priceless adventure.

How I Automated Tinder Using Artificial Intelligence: I got tired of swiping on dating apps. Rather than stop using apps completely, I decided to use machine learning to automate the swiping.

Interviews I’ve Done

This is my most popular interview ever (20k+ views) on how to hack the job hunting process with no experience. This interview is targeted towards data scientists, but applies to all jobs:

I did an interview with Ken Jee (172k + subscribers) talking about the process of learning, my tinder AI project and much more:

I also talk with Data Science Jay about using data science, tracking job metrics to land the a data science job. Plugging Jay’s company, Interview Query, if you’re looking for interview prep!

I also did an interview with The Artists of Data Science. Check out the beginning of the interview for a sneak peek into my freestyle rap alter-ego! Click image for the link.

Technical Content

Improving Experimental Power through Control Using Predictions as Covariate (CUPAC): At DoorDash, we pioneered a new technique called CUPAC, which uses a machine learning prediction as a covariate when analyzing experiments. In offline simulations, we saw a 33% improvement in the power of our experiments.

R Fundamentals: Building a Simple Grade Calculator: A beginner tutorial on the fundamentals of R by building out a simple grade calculator. No experience required!

How to use if-else statements and Loops in R: Building off the beginner tutorial in R, this tutorial teaches you how to use if-else statements and loops in R. Make sure you go through the fundamentals tutorial first.