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What is the difference between data scientist and statistician? Have you ever seen data scientist, like with a PhD? Have you ever seen statistician with PhD lik

What is the difference between data scientist and statistician? Have you ever seen data scientist, like with a PhD? Have you ever seen statistician with PhD like https://statistics.wharton.upenn.edu/programs/phd/ https://statistics.wharton.upenn.edu/programs/phd/ ?

aninteger 13y ago
My best guess is that a statistician is a focus more on mathematics/pure statistics while data scientist is involved in more algorithms.. but the lines are blurred and I don't know what we would call people like Nate Silver. According to Wikipedia he's a statistician.
sgt101 13y ago
Statisticians are usually preoccupied with understanding the properties of a data set. There is a penumbra of activities which are associated with statistics that have become relatively more important as technology has changed - getting the data, managing the data and transmitting the understanding of the data to humans. Most of the people who successfully market themselves as pucker data scientists do have Ph.D's - often in Machine Learning, but sometimes in Maths or HCI.
SandB0x 13y ago
"Data Scientist" is to "Statistician" as "Coding Ninja" is to "Developer".
jebus989 13y ago
"Data scientist" just sounds more impressive than analyst and less boring than statistician.
brg 13y ago
It is simple to see the progression of the nomenclature; companies used to employ staticians, then analysts, and now data scientists. There are subtle differences that have evolved recently, today's data scientists often are employing ml and spending time on feature engineering.
nfoz 13y ago
Data scientist does not imply mathematical rigour or professionalism.
- darkhorn 13y ago
  That's the problem, calling them scientist.
agibsonccc 13y ago
I would like to add where I teach[1], our data scientists get hired at places like tesla . Many of our students tend to be bachelors or phds. You don't need an phd to do data science. It is more about hands on skills. [1] http://www.zipfianacademy.com/ http://www.zipfianacademy.com/ Edit: Cabinpark is right and I should clarify. Statisticians typically don't have the proper computer science fundamentals to be able to deal with the programming required to run the right experiments. They may have an understanding of the distributions, t tests, ... but may not be able to use the tools out there that the broad field of data science requires.
- cabinpark 13y ago
  That doesn't answer the question. When I hear the term data scientist, I assume that the person has extensive training and background in statistics and mathematical modeling. I work with large data sets all the time as a scientist and can run all the standard statistical tests but I would hardly consider myself a data scientist.
  - agibsonccc 13y ago
    Realistically, most "data scientists" that people hire aren't going to have that full background. I think the problem with a lot of data science teams out there today is the hiring. Not a lot of people understand what the role of a data scientist should be and they expect these people who can do hadoop end to end, extensive CS skills, know all of the latest advanced machine learning algorithms, and know stats like the back of their hand. Many employers will not need or use that full pipeline, and if they do, they are probably capable of hiring hadoop engineers as well as more traditional analysts who are deeper in the math with the models. That analyst is someone with a specialized background and some form of training in scientific computing. This does not need to be a full blown masters/phd. Realistically, you can get away with having a decent programming background, a clue about the landscape of the machine learning algorithms, and enough statistics to know when you're going down a rabbit hole with respect to research. I think it more comes down to having the right mindset with problem solving. Much of this is also going to be domain specific. The term data science is ambiguous at best, as it is a new field. I think over the next few years we'll come to see more specialized roles over time that will help clarify the sandbox that is data science vs data engineering among other disciplines.
noelsusman 13y ago
http://www.cseprograms.gatech.edu/csephd http://www.cseprograms.gatech.edu/csephd I think a subset of that program would be rightly called data scientists. There is significant overlap, but statisticians are stronger in mathematical theory while data scientists are stronger in programming and computation. At least that's how I see it. It's not particularly well defined at the moment, and a lot of people throw these words around because they're new and fun.

aninteger 13y ago

My best guess is that a statistician is a focus more on mathematics/pure statistics while data scientist is involved in more algorithms.. but the lines are blurred and I don't know what we would call people like Nate Silver. According to Wikipedia he's a statistician.

sgt101 13y ago

Statisticians are usually preoccupied with understanding the properties of a data set. There is a penumbra of activities which are associated with statistics that have become relatively more important as technology has changed - getting the data, managing the data and transmitting the understanding of the data to humans. Most of the people who successfully market themselves as pucker data scientists do have Ph.D's - often in Machine Learning, but sometimes in Maths or HCI.

SandB0x 13y ago

"Data Scientist" is to "Statistician" as "Coding Ninja" is to "Developer".

jebus989 13y ago

"Data scientist" just sounds more impressive than analyst and less boring than statistician.

brg 13y ago

It is simple to see the progression of the nomenclature; companies used to employ staticians, then analysts, and now data scientists. There are subtle differences that have evolved recently, today's data scientists often are employing ml and spending time on feature engineering.

nfoz 13y ago

Data scientist does not imply mathematical rigour or professionalism.

darkhorn 13y ago
That's the problem, calling them scientist.

agibsonccc 13y ago

I would like to add where I teach[1], our data scientists get hired at places like tesla . Many of our students tend to be bachelors or phds. You don't need an phd to do data science. It is more about hands on skills. [1] http://www.zipfianacademy.com/ http://www.zipfianacademy.com/ Edit: Cabinpark is right and I should clarify. Statisticians typically don't have the proper computer science fundamentals to be able to deal with the programming required to run the right experiments. They may have an understanding of the distributions, t tests, ... but may not be able to use the tools out there that the broad field of data science requires.

cabinpark 13y ago
That doesn't answer the question. When I hear the term data scientist, I assume that the person has extensive training and background in statistics and mathematical modeling. I work with large data sets all the time as a scientist and can run all the standard statistical tests but I would hardly consider myself a data scientist.
- agibsonccc 13y ago
  Realistically, most "data scientists" that people hire aren't going to have that full background. I think the problem with a lot of data science teams out there today is the hiring. Not a lot of people understand what the role of a data scientist should be and they expect these people who can do hadoop end to end, extensive CS skills, know all of the latest advanced machine learning algorithms, and know stats like the back of their hand. Many employers will not need or use that full pipeline, and if they do, they are probably capable of hiring hadoop engineers as well as more traditional analysts who are deeper in the math with the models. That analyst is someone with a specialized background and some form of training in scientific computing. This does not need to be a full blown masters/phd. Realistically, you can get away with having a decent programming background, a clue about the landscape of the machine learning algorithms, and enough statistics to know when you're going down a rabbit hole with respect to research. I think it more comes down to having the right mindset with problem solving. Much of this is also going to be domain specific. The term data science is ambiguous at best, as it is a new field. I think over the next few years we'll come to see more specialized roles over time that will help clarify the sandbox that is data science vs data engineering among other disciplines.

noelsusman 13y ago

http://www.cseprograms.gatech.edu/csephd http://www.cseprograms.gatech.edu/csephd I think a subset of that program would be rightly called data scientists. There is significant overlap, but statisticians are stronger in mathematical theory while data scientists are stronger in programming and computation. At least that's how I see it. It's not particularly well defined at the moment, and a lot of people throw these words around because they're new and fun.