What do you believe are the major differences between an Analyst and a Data Scientist? Do you consider the two synonymous?

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An analyst can actually explain data to humans. A data scientist spends their days talking to numbers. 😂

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Analyst do descriptive analytics while scientist do descriptive, predictive and prescriptive.

likesmart

Also data scientist and their roles come in a very wide spectrum while analyst roles will be pretty similarly across companies/industries.

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I do think data scientists usually hold master or doctoral degrees in math/stats as well

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The analyst interprets what the Data Scientist discovered. And then prepares an insight report.

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The label "data scientist" has been bastardized over the years. Agencies like to sell the term when in reality 99% of most agencies tend to deliver more traditional analytics services (e.g. measurement), which are valuable, but is not true data science. Data scientists are expected to have a much deeper expertise manipulating both unstructured and structured data. They should also have some level of knowledge and experience of various statistical techniques. The rise of data science has come with the increase in volume and sources of data. It's messy. Analysts and Data Scientists are both valuable and job descriptions can overlap a bit, but the services they provide are different.

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@PS 1, actually big tech is a big part of the problem with the confusion between Analyst and Scientist. Company’s like Spotify and Facebook rebranded all their Data Analyst roles as Data Scientist. So you can easily be a “Data Scientist” that is just building dashboards and doing traditional analyst work.

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I consider them synonymous. Life would be too boring to be one or the other.

A good analyst would dig deeper, because being inquisitive is who they are... that's why they can uncover the "why".

A good data scientist is curious as well: digging deeper and deeper behind black boxes, going back to the business question to link the models to the problem.

They both crossover... and they should.

likesmart

In a large agency they are generally different because you have the ability to develop specializations across your team. In a small agency you tend to need more multidisciplinary staff and the lines blur. This also typically includes blurring the lines with data engineers, architects and so on for smaller or less well organized agencies. Accordingly, the titles often don't translate well from agency to agency and you'll see a lots of inconsistencies. On the plus side - this gives agencies doing it really well a strong point of differentiation.

likehelpful

What agencies do you think do it well, SVP?

Analysts can often perform some jobs of a data scientist. And similarly data scientists may also interpret and tell stories with their data. Data scientists generally go deeper with data often working with big data performing algorithms like machine learning and predictive models.

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One major difference is the amount of time each spends building models and data wrangling versus driving decisions and translating data to decision makers. Both need many of the same skills but the data scientist is going to be better at crunching the data, designing the best model and wrangling it, while the analyst is going to be better at defining the business problem, analyzing the output and visualizing the data to provide insights to management.

A way to think about the analyst is as a bridge between the MBAs and the Quants. The analyst speaks both languages. It is why business analytics is in the business school more often than in tech programs.

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Last time I checked "MBA" isn't a position... All this BS is just an excuse for diversifying skillsets that one person should be able to cover in an agency setting - because what we do isn't that groundbreaking. But instead everyone wants to avoid the hard work of actually being able to communicate and do math at the same time.

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A PHD

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I think those are the true data scientists. I would love to give them that honor.

Imh data scientist is a broader term just became more popular these days. It depends on how the company defines it. It can be one or more of the following: analyst, machine learning scientist, data engineer, statistician, etc.

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I’m in banking and here’s how my team is structured. Each team has 2 analysts and 1 data scientist.

From what I’ve known and seen it’s just a matter of YOE. What role you land in!

Probably a year from now, I’ll become a “data scientist” and the data scientist would be promoted to become a manager.

P.S: this is banking, things I’m saying might be outdated.

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