I like to solve problems. How do I get paid to do that?
February 7, 2016 8:40 PM Subscribe
I've flip flopped on what I want to go to school for and/or what kind of career track I want to aim for. Can you help?
Like it says on the tin, I like to fix things. Right now I'm in a Quality Assurance type role in a call center. There's a lot of data floating around and not many people who know how to organize it. I've spent the last six months making Excel dashboards, creating SQL queries and VBA macros, and analyzing data.
I love all of these things. Like a lot. I thought I wanted to be a data analyst at one point, and even reached out to a few MeFi people for advice on that career track (thanks Ruthless Bunny!). But now I'm not so sure.
I really like working with data, finding ways to extrapolate answers from the data you have, getting answers to your boss, finding trends, etc. But I also am loving learning SQL and figuring out how databases work. My pet project right now is building a database and a front end application (as specifically warned against in this question). And last but probably most, I love Excel. I love building new projects, finding ways to present data in ways that make sense. Learning new ways to make my formulas more efficient, cleaner, and more adaptable to change.
So what kind of job can I get where I do all of that? Will being a data analyst let me do at least most of that? Will I get bored if I pursue a career as a DBA? Can I just sit around and wait for people to pay me to fix their Excel problems?
I know this is a big question. I've been flip flopping for the last six months on what major to pursue in college, and what kind of personal projects will best help me later on. I feel like I don't know jack about real world careers and I don't want to make decisions now that I will regret later on.
Like it says on the tin, I like to fix things. Right now I'm in a Quality Assurance type role in a call center. There's a lot of data floating around and not many people who know how to organize it. I've spent the last six months making Excel dashboards, creating SQL queries and VBA macros, and analyzing data.
I love all of these things. Like a lot. I thought I wanted to be a data analyst at one point, and even reached out to a few MeFi people for advice on that career track (thanks Ruthless Bunny!). But now I'm not so sure.
I really like working with data, finding ways to extrapolate answers from the data you have, getting answers to your boss, finding trends, etc. But I also am loving learning SQL and figuring out how databases work. My pet project right now is building a database and a front end application (as specifically warned against in this question). And last but probably most, I love Excel. I love building new projects, finding ways to present data in ways that make sense. Learning new ways to make my formulas more efficient, cleaner, and more adaptable to change.
So what kind of job can I get where I do all of that? Will being a data analyst let me do at least most of that? Will I get bored if I pursue a career as a DBA? Can I just sit around and wait for people to pay me to fix their Excel problems?
I know this is a big question. I've been flip flopping for the last six months on what major to pursue in college, and what kind of personal projects will best help me later on. I feel like I don't know jack about real world careers and I don't want to make decisions now that I will regret later on.
Degree advice - Engineering. Some kind of engineering. Or science. Data analysis can be a fine kind of problem solving work, so can certain types of hardware engineering etc. But what matters more than the degree will be the specific positions (company, manager, team), so I strongly recommend a broad and strong degree like CS or physics (or another basic science) or maybe some sort of mechanical degree that will make people think, "yeah, this one looks smart and flexible, capable of handling some challenging problems" in the early stages of hiring. (Once you have ten years of experience, sure, degrees don't matter so much and obviously you're capable of finding that sort of work to do anywhere. But those first few years are a lot easier and nicer if you don't have to prove your basic competence over and over again.)
"I love figuring stuff out and solving problems" is a really broadly applicable skill set. But you don't want to pigeonhole yourself into a single function because that leads to solving the same problem over and over again with no chance to learn new things.
Though: if you are finding ways to do a satisfying amount of learning/creating/developing work in a "call center qa" type position you may be one of those who will thrive regardless. Seems like it so far.
posted by Lady Li at 9:14 PM on February 7, 2016
"I love figuring stuff out and solving problems" is a really broadly applicable skill set. But you don't want to pigeonhole yourself into a single function because that leads to solving the same problem over and over again with no chance to learn new things.
Though: if you are finding ways to do a satisfying amount of learning/creating/developing work in a "call center qa" type position you may be one of those who will thrive regardless. Seems like it so far.
posted by Lady Li at 9:14 PM on February 7, 2016
the full-time DBAs i know and work with are not-at-all involved in data modelling or analysis. that role is actually more concerned with things like: disk config, fail-over, backups, security, optimizations, clustering...
the people i know who do statistics and data analysis are MS/PhD in statistics or applied physics. they do their magic in R or python and have no user interaction at all. in a lot of cases, they get handed a schema and told to answer a specific question. they split that into two parts (1) can that be answered with the data we have? (2) if no, what can we answer?
I love...Learning new ways to make my formulas more efficient, cleaner, and more adaptable to change.
more efficient - Big O notation is a formalized approach to algorithmic efficiency
cleaner - OOP has the Single Responsibilty Principle (SRP)
more adaptable to change - 'loose coupling' is achieved by consistent application of SOLID
as a-person-who-hires-developers, i think there are two big hurdles for you:
1) limited development experience (excel) - you've gotta break out of the how-can-i-use-a-spreadsheet-to-solve-this and into the what's-the-right-tool-for-the-job. dig into python, javascript, and c#/java for scripting, front-end, and back-end respectively. learn the basics and sql syntax of any enterprise rdbms.
2) one-man-shop - i'm betting you only have ever worked 'your way' without direction or peer collaboration. do you know about version control? ever thought of looking at some OSS on github?
i have a similar beginning: i began by optimizing digital production tasks using shell scripts, then macros inside a gis tool, then component reuse, then web...my training is as an EE, but 20 years into a software career, i now lead two teams in enterprise application development.
your own curiosity and the guidance of a few well-chosen mentors is a better guide than any curriculum (though i see a lot of value in a good engr or cs degree).
these days, software developers are expected to to determine the database type (e.g. rdbms, nosql, object db...), model the domain, and either write the code, queries/SPs, or leverage an ORM. excel could be part of an approach, but consider the elements that make up a quality development effort: bug tracking, unit test, UI test, load test, task tracking, version control systems, disaster recovery/continuity of operations, deployment engineering...what are you going to do about security, logging, exception handling, instrumentation? there is more to this than a functionally correct macro. only you know if that's a good road for you to explore.
posted by j_curiouser at 9:36 PM on February 7, 2016 [5 favorites]
the people i know who do statistics and data analysis are MS/PhD in statistics or applied physics. they do their magic in R or python and have no user interaction at all. in a lot of cases, they get handed a schema and told to answer a specific question. they split that into two parts (1) can that be answered with the data we have? (2) if no, what can we answer?
I love...Learning new ways to make my formulas more efficient, cleaner, and more adaptable to change.
more efficient - Big O notation is a formalized approach to algorithmic efficiency
cleaner - OOP has the Single Responsibilty Principle (SRP)
more adaptable to change - 'loose coupling' is achieved by consistent application of SOLID
as a-person-who-hires-developers, i think there are two big hurdles for you:
1) limited development experience (excel) - you've gotta break out of the how-can-i-use-a-spreadsheet-to-solve-this and into the what's-the-right-tool-for-the-job. dig into python, javascript, and c#/java for scripting, front-end, and back-end respectively. learn the basics and sql syntax of any enterprise rdbms.
2) one-man-shop - i'm betting you only have ever worked 'your way' without direction or peer collaboration. do you know about version control? ever thought of looking at some OSS on github?
i have a similar beginning: i began by optimizing digital production tasks using shell scripts, then macros inside a gis tool, then component reuse, then web...my training is as an EE, but 20 years into a software career, i now lead two teams in enterprise application development.
your own curiosity and the guidance of a few well-chosen mentors is a better guide than any curriculum (though i see a lot of value in a good engr or cs degree).
these days, software developers are expected to to determine the database type (e.g. rdbms, nosql, object db...), model the domain, and either write the code, queries/SPs, or leverage an ORM. excel could be part of an approach, but consider the elements that make up a quality development effort: bug tracking, unit test, UI test, load test, task tracking, version control systems, disaster recovery/continuity of operations, deployment engineering...what are you going to do about security, logging, exception handling, instrumentation? there is more to this than a functionally correct macro. only you know if that's a good road for you to explore.
posted by j_curiouser at 9:36 PM on February 7, 2016 [5 favorites]
Construction estimating, if you thrive under immense pressure.
posted by halogen at 11:04 PM on February 7, 2016 [1 favorite]
posted by halogen at 11:04 PM on February 7, 2016 [1 favorite]
Business analyst at a market research firm.
posted by rhizome at 1:01 AM on February 8, 2016 [1 favorite]
posted by rhizome at 1:01 AM on February 8, 2016 [1 favorite]
You want to do what I do. I'm a Consultant for a large consultancy firm. We do recruiting on college campuses. I'll send you a link.
While I'm a Salesforce specialist, we recruit folks straight out of school and train them. In addition to technology-emerging markets (my thing) there's operations consulting, strategy consulting and management consulting.
I sent you a MeMail. If you want, when you're ready, you can use me as your referral person.
posted by Ruthless Bunny at 4:32 AM on February 8, 2016 [4 favorites]
While I'm a Salesforce specialist, we recruit folks straight out of school and train them. In addition to technology-emerging markets (my thing) there's operations consulting, strategy consulting and management consulting.
I sent you a MeMail. If you want, when you're ready, you can use me as your referral person.
posted by Ruthless Bunny at 4:32 AM on February 8, 2016 [4 favorites]
Be a data scientist! Data scientists do data analysis, try to identify trends and answer questions using big data sets, and communicate the results in a way that people can understand. This is an in-demand field and there are all sorts of programs and training courses popping up to teach you how to do it. You will need to learn a statistical programming language (R is currently the most popular).
posted by chickenmagazine at 5:21 AM on February 8, 2016 [1 favorite]
posted by chickenmagazine at 5:21 AM on February 8, 2016 [1 favorite]
If you like math and programming as well as data analysis, the medical school where I work has a department full of biostatisticians whose sole purpose is to turn research data into useful information.
posted by The Elusive Architeuthis at 6:49 AM on February 8, 2016
posted by The Elusive Architeuthis at 6:49 AM on February 8, 2016
For your degree program, consider also actuarial science. It's useful in many more fields than insurance, e.g., if you want to be a quant in finance, marketing, etc.
posted by carmicha at 8:14 AM on February 8, 2016 [2 favorites]
posted by carmicha at 8:14 AM on February 8, 2016 [2 favorites]
I work on what they are these days calling "big data" backend systems. It's very programming heavy work, with minimal analysis. The interesting and fun problem-solving part of the job is thinking about how the data models of different DBs will fit together to make our system faster/better/cheaper to host, or enable a wider range of use cases that the business cares about. This is what software engineering is all about – how to build the system that meets your needs. It is a lot of testing, refactoring (moving parts of the system around), re-testing, measuring results, etc. Pretty similar to what you might expect any engineer to be doing. DBAs are more on the operations side of things. They keep the system running and know all the ins and outs but don't usually actively build new components.
From what I've seen, there isn't a lot of work you can get where you're just looking at the numbers or making formulas in spreadsheets. There is some very high-level work like that, but it is typically done only by a small number of PhD level statisticians at the biggest tech companies (Apple, Microsoft, etc.) who have those kind of resources. I think if you want to work with data but you don't want to be an engineer, your best bet is probably to be a Business Analyst (BA). You would be reporting to the business side of the company, interpreting results of what the engineers have built, and helping to inform the next round of development. I think BAs usually have some kind of CS-related background, but even math or some other hard science would be relevant. They don't need to be technical masters, just be proficient enough to translate to and from the engineers, so to speak.
Actually I do know someone who works in finance and apparently everything they do runs in very complex Excel macros. So you might look into that.
posted by deathpanels at 8:28 AM on February 8, 2016
From what I've seen, there isn't a lot of work you can get where you're just looking at the numbers or making formulas in spreadsheets. There is some very high-level work like that, but it is typically done only by a small number of PhD level statisticians at the biggest tech companies (Apple, Microsoft, etc.) who have those kind of resources. I think if you want to work with data but you don't want to be an engineer, your best bet is probably to be a Business Analyst (BA). You would be reporting to the business side of the company, interpreting results of what the engineers have built, and helping to inform the next round of development. I think BAs usually have some kind of CS-related background, but even math or some other hard science would be relevant. They don't need to be technical masters, just be proficient enough to translate to and from the engineers, so to speak.
Actually I do know someone who works in finance and apparently everything they do runs in very complex Excel macros. So you might look into that.
posted by deathpanels at 8:28 AM on February 8, 2016
I'm a data engineer and I like to do all the things you mentioned, so I thought I'd mention it. But data scientists and data analysts have a lot of overlap with data engineers, so those are also good suggestions. It's a nebulous enough field that what an engineer does at one small company may actually be done by a scientist or analyst at a larger (or just different) company.
posted by thewumpusisdead at 12:16 PM on February 8, 2016 [1 favorite]
posted by thewumpusisdead at 12:16 PM on February 8, 2016 [1 favorite]
Database developer or Business Analyst roles sound right for you. That's what I do for a living. If you find yourself really liking the technical side of things, becoming a SQL developer (not a DBA), data engineer, or data scientist could be cool too.
posted by Aizkolari at 12:33 PM on February 8, 2016
posted by Aizkolari at 12:33 PM on February 8, 2016
See what I mean about not just one job/title?
I'm a manufacturing engineer, myself, and there's a ton of figuring out how to look at a problem to understand what's going wrong, creating new tools and macros/parsers for the technicians to use to process test results, monitoring diagnostics for predicting maintenance needs, etc.
In the creative/developing stage it'd be great for you. But if you found the same title somewhere else with a more restrictive corporate culture it could easily be a job that has more 'modify this widget to be half the size of the last widget' or 'run this test that the design engineer created that pops out "pass" or "fail" and don't ask questions' or 'fill out this ream of documentation about this failed component'.
posted by Lady Li at 9:00 AM on February 9, 2016
I'm a manufacturing engineer, myself, and there's a ton of figuring out how to look at a problem to understand what's going wrong, creating new tools and macros/parsers for the technicians to use to process test results, monitoring diagnostics for predicting maintenance needs, etc.
In the creative/developing stage it'd be great for you. But if you found the same title somewhere else with a more restrictive corporate culture it could easily be a job that has more 'modify this widget to be half the size of the last widget' or 'run this test that the design engineer created that pops out "pass" or "fail" and don't ask questions' or 'fill out this ream of documentation about this failed component'.
posted by Lady Li at 9:00 AM on February 9, 2016
This thread is closed to new comments.
Look at Business Analytics. I work for a Fortune 500 company, and there are very highly paid consultants from KPMG and the like whose primary function is to do long term Business Analytics projects for us. They do pretty much exactly what you describe loving.
posted by erst at 9:12 PM on February 7, 2016 [9 favorites]