Data Scientist

Python SQL Machine learning
Craft Coffee
New York, NY, United States
Full Time
Visa sponsor
Work Remote
Salary: $75,000.00 - $145,000.00

About Craft Coffee:

Craft Coffee is fundamentally rethinking the $71B coffee industry. We're the first true tech startup in coffee.

About the job:

Music, movies, art, dining, dating, advertising. You name it, somebody is applying data science to it. Except coffee. Why has this $71 billion global industry gone entirely untouched by data science?

Because coffee is just coffee, right?

Wrong! We know from years of operating the only real tech startup in this space that coffee consumption is deceptively complex. The existing approach is completely broken.

The challenge...

Hundreds of millions of people drink coffee every day. But the industry is entirely upside down. Each company decides how they think coffee is supposed to taste and then they dictate their preferences to their customers as if it's objective truth. Well, it's not. They just aren't very original thinkers. Our goal is to radically change this. We propose that our customers can dictate their personal taste preferences to us, and that we can understand those preferences and personalize their experiences using technology. This is why we’ve built the Coffee DNA Project into the core of our service. We are running the most ambitious experiment ever into understanding the taste preferences of coffee drinkers.

The opportunity...

This is a rare opportunity to dive deep into an untouched domain. There's no roadmap for what we're doing in coffee. Until now, the coffee industry has relied on subjective sensory methods, derivative thinking and bullshit marketing. But we know that there are objective truths behind coffee preferences, and we're building the first quantitative model to understand these truths. Our data scientist will work closely with our coffee director and head roaster to figure out what data points really matter (and which ones don't).

We're building an arsenal of measurement tools that other coffee companies don't have. This will let us use hard science in unprecedented ways to answer questions that are normally glossed over with subjective explanations. Such as:

  • Is there a correlation between the moisture content of green coffee and how likely someone is to enjoy it?
  • How does the decomposition of organic compounds affect the ability to enjoy a particular coffee?
  • Why do some people love dark roast while others can't stand it?

Who we're looking for...

Our ideal candidate could have a PhD in machine learning and years of experience with the Hadoop stack, but we're also open to other profiles. We're not Pandora. Yet. Since we're early stage, we need you to move quickly, collaborate efficiently, and internalize our product vision completely. There's no room for silo'd academic-style research here. Analysis and insights aren't enough. We need someone who will create tight feedback loops with our tech and product teams to drive iterative product improvements. In turn, product improvements will provide the data needed to test hypotheses.

You may be right for the job if...

  • You're hungry for the opportunity to dive deep into an untouched domain. The unknowns and challenges excite you. You don't want to waste your time at some paint-by-numbers advertising company optimizing display ads.
  • You're great at finding a signal in the noise, even when you're not sure what signal you're looking for. On the flip side, you know when there's no signal to be found and you need to cut your losses.
  • You have no problem testing multiple hypotheses at the same time. There's a lot to learn, and the best time to learn it was yesterday.


  • Very excited to do a deep dive on coffee knowledge. We need someone who is endlessly curious about the domain.

  • Experience with SQL databases.

  • Experience with Python or Java.

  • Experience with R, Matlab, or other scientific computing language.

Bonus points

  • Bachelor's degree (or higher) in a data science-related field.
  • Experience with machine learning and recommendation engines.
  • Experience managing Hadoop clusters - initial implementation and/or scaling clusters through rapid growth.

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