
Ask HN: Data Scientist vs. Machine Learning Engineer - jpiabrantes
What are the major differences between a data scientist and a machine learning engineer?<p>Differences in education, tools used, functions within a team, etc.
======
dsacco
I don't think there's a hard and fast rule. This is similar to the term
"quant", which can mean anything from a research scientist using applied
mathematics to develop new models and strategies, to a developer who works on
the software used by research scientists. It's (deliberately) fuzzy.

In the case of data science and machine learning, my _experience_ is that data
scientists are frequently more involved in munging data, warehousing and
writing SQL code for analysis, while machine learning engineers write software
or models for interacting with the data and making predictions.

Again, I don't think it's a binary distinction, but personally I'd expect a
data scientist to be working mostly with databases and data directly and an ML
engineer to be developing software and forecasting models.

Practically speaking the education and background for the two is similar in
that they're fundamentally not _research_ oriented positions, they're
engineering positions, which means they're accessible to someone with software
engineering experience but not a significant mathematics or statistics
background. On the converse, a machine learning researcher would be
significantly more theoretical - still writing code, but mostly working with
abstractions and models, not doing most of the heavy lifting implementation
wise. A position like this will be significantly less accessible to, say, most
of Hacker News, as you'll generally need an MSc at minimum to be a competitive
candidate. Although obviously there are exceptions.

As a piece of advice, I would urge you to consider most of these specialized
titles to be marketing terms. If you have an opportunity to work in either
role, make sure you're very clear about the actual responsibilities involved.
It's a lot easier to throw someone an impressive title than it is to throw
them impressive responsibilities or an impressive salary.

------
iamwil
I'd always thought of data scientists producing mostly analysis and reports,
and sometimes products, and machine learning engineers producing mostly
products that do predictions.

But in practice, they're probably not too different from each other. They both
need to get data, clean data, analyse data, produce a model that predicts.

In addition, sharing datasets is probably something they have to do:
[https://blog.helmspoint.com/posts/2017/09/05/sharing-
machine...](https://blog.helmspoint.com/posts/2017/09/05/sharing-machine-
learning-datasets.html)

------
edimaudo
Not much really much difference but an ML Engineer would focus more on
building software and data pipelines

