Job Titles & Descriptions

YES! Saw that today and laughed out loud!

I pretty much agree with Hadley on that, but would also want some criteria about using the scientific method. I feel like Data Science without the science is just data fidget spinning. Programming data analysis is great for tons of reasons (but mainly reproducibility IMO), but if you don't follow the scientific method you're opening up yourself to potential bias and failure. I don't think data science needs to be super complicated for it to be super valuable, which seems to be the opposite assumption I get from most people. As long as you state your assumptions and show your work, you're already making great progress. To me, programming is a great tool for showing your work.

For reference, from Khan Academy

1. Make an observation.
2. Ask a question.
3. Form a hypothesis, or testable explanation.
4. Make a prediction based on the hypothesis.
5. Test the prediction.
6. Iterate: use the results to make new hypotheses or predictions.

I'm a senior associate (meaningless, I know) in a research sciences department. They mostly work in SPSS, which I've picked up as I've helped expand into more of an R-focused direction. We don't work with ~big data~ but we do modeling and more and more ML-type things, even if it's on a smaller scale. I definitely have a complex about it, but I get to learn a ton on the job and love that.

When I was searching (making the transition out of a communications job) I thought I wanted to work with polling data, so I applied to anywhere that was hiring that did that kind of work, which is how I ended up where I am now (and have done no polling work since--we're market research). It was a lot of luck, in my case, I think.

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Just as a follow up, when I got to voice my suggestion for title, I chose Data Analyst. Similarly to @scottbrenstuhl, I like the vagueness of it because I work on a lot of different types of projects, not always falling into the realm of Data Science. I also liked it because this is my first job as an adult and I feel it gives a general idea of what I do without implying that I have a lot of experience.


I think this is the first time I knew for sure something I said was helpful to someone on the internet. WHAT A TIME TO BE ALIVE! So glad I could help :smile:, Enjoy the new title!

Just a potential new title. Data Analyst is just my opinion. It still has to go through HR, who will have their own opinions, and the be approved by my organization's board. So I'll find out in a month or two, hopefully before the end of the year.

thanks for the thread, y'all! as @scottbrenstuhl and @dlsweet have mentioned, i too like the vagueness of "data analyst". it also seems a bit more "direct"(?) and not so hype-y.

any thoughts on the title "quantitative analyst". i like this for the same reasons but it also seems to capture the mathyness that i love (oh so much) in my work. i know it has financial connotations, but i'm surprised that i don't see this title more in the data space.

We went though several iterations. I now have Data Associates, Sr. Data Associates, and Director of Data.

This mirrors our levels for other roles (title, sr, dir). Because these roles involve integrations, analysis, etc we decided just “data” is enough.

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From the perspective of the field of statistics, "analyst" is somewhat problematic in that field due to its historical association of "statistical analyst" with an entry-level/bachelors position. Professional-level/advanced positions are just "statistician". That may be part of the source for an initial preference of "data scientist" over "data analyst".


This is a really good point, and part of why I like Data Analyst the best. This is my first job and I've only been working for roughly 3 months, so I thought that analyst captured that it was a more entry-level position.

That's one of those jargon words that can be a contronym depending on your audience. :roll_eyes:

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I'm resurrecting this topic, as I need y'all's advice.
What are the typical titles in your Analytics / Data Science departments / teams? Could you name a few roles and who do they report to?

Do you have title like Data Analyst, Business Intelligence Analyst, Business Analyst, and how do you distinguish between them?

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Let me expand. I currently hold a title of Manager, Business Intelligence. Before that, it was Business Intelligence Analyst. And before that, it was Data Analyst. Promoted every time.

In other words, my management thought that Business Intelligence Analyst is senior to Data Analyst (which I now tend to disagree with, but looking for comments from you all)

Also, it seems to me that my title of Manager, Business Intelligence doesn't capture everything that I do, e.g. crafting a vision of data storage and architecture, doing a ton of SQL, crafting the data strategy and executing on it, and also actually working in R and doing Machine Learning. I'm making a case to rename the team from Business Intelligence to Data and Analytics, which for me would mean the title of Manager of Data and Analytics.


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When negotiating job titles, I've found that what's been most helpful for me is to look at what job I'd like next (whether within or outside the current organization), and use that to negotiate my current job title.

My personal experience is that titles carry the most weight within your current organization, due to a lack of standardization across organizations. The parts of titles that tend to most readily translate to other organizations are the leadership designations (Manager, Director, VP, C-suite).


Just as a follow-up to everyone who helped me when I was negotiating titles, I am now a Data Analyst!!! This is the title that I was hoping for so my negotiations went well!


In turn, I talked to HR and my manager about getting rid of "Business Intelligence" altogether. Wrote up my own "Manager, Data & Analytics" job description yesterday!


I just shipped off a new description of my job to HR as well, hoping for the nice shiny new title of "Assessment, Data and Analytics Specialist". Cheers to us :beers:!


At Lyft, we’re rebranding our Data Analyst function as Data Scientist, and our Data Scientist function as Research Scientist. In this short post, we describe the reasoning behind the change, which we believe will set Lyft up to make better decisions and build better products as we scale.


Slightly different view...

Data Analyst, Data Scientist, Data Manager, Business Intelligence Analyst, Data Consultant, Data Visualisation Engineer, Insight and Analytics Consultant, Machine Learning Engineer.

There has been a proliferation of data based job titles and whilst I can perfectly understand titles that maximise salary, or optimise your searchability on LinkedIn, I think far too much weight is put on job titles, when what matters is skills and what you can bring to the table.

I'm not all together too sure that job titles are that transferable and comparable any more (see the bank's job titles of "Vice-Presidents" for relatively junior employees, or the Big Four professional services firms with the vague job titles of "Senior Associate" or "Associate Director").

Maybe my opinion will change, but I'm not too bothered what my job title is. I'm far, far more bothered about the work I'm doing, the skills I'm learning and the people I'm working with. My job title is miles down the list of important considerations in my job.


I agree. I haven't been job-searching, but I imagine the best way to hire "data scientists" is similar to how software developers or artists are hired: portfolios of actual results.