[citation_please]

As someone who has been producing value in a data science/machine learning role for multiple years, it's disheartening to see comments that I may be blacklisted from positions due to "only" having a bachelor's degree.

Somewhat non-humbly, I was valedictorian at my high school, I triple-majored at a respectable Big 10 school, I actively use all 3 majors on a daily basis, in a foreign country, and sometimes in a language that is not my mother tongue (as an American).

I can't justify spending time and money on a master's degree (millennial wealth problems) where many courses would just be putting a formal, academic spin on ideas that I'm familiar with from a practical business-value-producing point of view.

Any advice on how I can effectively jump off the black-lists?

[dswalter]

If your target is a data scientist role at Google, you're probably going to want more schooling.

But if you've been producing value in a DS/ML role for years, you have experience, which is even more rare than some of the qualifications people are listing here.

If you can say "I created an anomaly detection system using isolation forests that 5,000 clients relied on for detecting market changes", there will always be places that want your skillset: it is kind of a new field, after all.

So the credential bloat at entry-level shouldn't really be an issue for you.

[laurentl]

Maybe a bit (a lot?) out there: why not go for a business degree instead, e.g. EMBA?

You mention “foreign country” so I’m guessing you can have access to good curriculums without paying the US premium on education (or just go for an online course).

Pros: the time and money is not “wasted” as you actually pick up new skills; the MBA card should be enough to trump any education requirement; and you become that most desirable of hybrids: the tech/data guy who can talk business (or vice versa).

Cons: significant time (and money) investment; doesn’t help you get expert DS jobs (you’d be aiming for team/program manager, consultant, etc)

My own experience: completed an EMBA in 2017. Ranked in FT’s top 10, the program cost was around 50 k€ (it’s increased a bit since) and I was able to get 25 k€ of outside funding. The program I followed lasts 2.5 years, meaning I was able to do it while keeping my job (and having a kid) without losing my sanity or my wife. Landed my dream job just before completing the curriculum for a nice 40% pay increase (not saying the EMBA alone had that effect, far from it —but it definitely helped).

[citation_please]

Huh. This is actually a route I hadn't considered. Thanks for pointing it out! I will definitely consider it as I continue researching my next opportunities...

[laurentl]

Glad that helped ;)

If you want more feedback on my personal experience, feel free to reach out (will update my profile with an email address).

[Synroc]

Is there any difference in terms of curriculum between the EMBA and the MBA? As in would people consider the EMBA a "lesser" MBA so to speak?

I'm an engineer looking at MBAs right now too, but it seems like a huge investment.

[laurentl]

EMBAs are usually part-time over 18 to 24 months, MBAs are full time over 12 to 24 months.

So an MBA naturally has a bigger (as in more in-depth) curriculum than an EMBA. It is also a significantly higher investment in terms of time and opportunity cost, since you're not getting paid during the program.

EMBAs compensate with 1) more experienced participants (so in theory you don't need the introductory classes) and 2) a lot of pre- or post-readings (e.g. my corporate law module was 12 hours in the classroom, but you were expected to have read the 400-page book, and the numerous case studies).

But the bottom line is that you don't go into as much detail as you would during a full-time program. OTOH, since EMBAs are attended by "senior" employees (managers / VPs / directors / etc), and because they're part-time, what you learn is usually directly relevant and applicable in everyday work - and you usually get to work on real-life problems (yours or your teammates) during classes.

I'm not the best placed to say whether an EMBA is considered a "lesser" MBA. They don't really fill the same niche. An EMBA is a career booster if you're say a technical manager and want to move into business or senior management. An MBA is when you haven't started working (or are still junior) and are looking for a fast track to C-level, or to work in a specific area (e.g. consulting, finance, etc.). So basically MBA vs EMBA is mainly a function of your current experience level.

[tixocloud]

In the same boat - technical background with MBA and managing

[Synroc]

What was your main reason to pursue an MBA with the technical background? I'm considering it too at the moment.

[tixocloud]

I had a dream of wanting to start a company one day and was interested in a more holistic understanding of the business side of things. I thought that it would add some credibility when speaking with business types but also uncover ideas to base the company on.

[Synroc]

Have you found it to be true? I guess in general have you found it to have been worth it.

One of my concerns is whether or not i’d be able to come back as an engineer as a fallback.

[tixocloud]

Personally, for me, I found it useful but not for the reasons of knowledge. The knowledge was good but the program helped to sharpen my speaking and thinking skills. It also broadened my mind to different perspectives - that the tech world that I come from is quite different to people outside of industry.

The classes and sessions have also made me think further and deeper about business, culture and management beyond the usual.

It also made me more disciplined - focus on the business not the product and technology. Used to waste countless hours building, researching with not much to show for.

It’s also given some confidence to speak to business types and connect with them at a deeper level while introducing technology to them.

You can most definitely fallback as an engineer but why are you thinking of an MBA in the first place? What’s your goal for pursuing one?

[SOLAR_FIELDS]

The UG online masters of computer science is a good option. Many people in this site speak highly of the curriculum[1]. Last time I checked the total for the entire curricula if you pass every course on the first try is around $7000. As a bachelor holder myself looking to break into some of these higher-salary and in-depth roles I’m certainly considering it. It’s even better if you have a company that will pay for it, and because it’s so cheap even the most meager offerings from companies will cover a good portion of it.

1: https://news.ycombinator.com/item?id=15018002

[citation_please]

Yeah I'm definitely familiar with the Georgia Tech offering. But my impression is that it will be a $7000 + $(my_hourly_rate) * (hours_spent) certificate that will only get me past the employers who have a "Select your highest degree level" drop-down on their application form. Is it that much more respected than a collection of MOOCs?

As someone who's also involved in hiring, if I see no industry experience + GA tech online degree it's still on an entirely separate tier than 2 years of industry experience. But that's my bias I suppose, and part of the reason that I'm not the only one on the hiring committee.

[jj12345]

Definitely biased, but here are some anecdotes/thoughts:

- I've found the rigor to be significantly more than most MOOCs, inline with other traditional grad courses I've taken.

- Some classes are hybrid, sharing the term with on-campus students.

- Not having finished the degree, my work as a data scientist has significantly benefited from the coursework. This is not to say that it wouldn't have benefited from other, non-GT coursework.

[bobmarley1]

That's rather sad considering the degree isn't going to say Online and Georgia Tech is top 10 in the world in Computer Science and online or not that credential carries real weight for people in the know.

[citation_please]

Well I'm not the one who does resume sorting, so usually if it makes it to my desk I know there's a good chance they're qualified. If you give me (personally) two resumes, one with a master's degree from almost anywhere, and one with two years of experience doing /exactly/ what we do, I'll choose the latter first. At this point, master's degrees don't carry the weight they used to in my mind based on (1) people I've interviewed (2) my coworkers and (3) my friends and acquiantances.

[treyfitty]

UG and GaTech are two different schools

[madcaptenor]

I'm not even sure what school "UG" refers to. (People generally call the University of Georgia "UGA".)

In any case, the program here is from Georgia Tech.

[apohn]

>Any advice on how I can effectively jump off the black-lists?

Find a decent hiring manager who has actually done some hands on Data Science/Analytics work and knows what skills/thinking are actually required. Lots of Data Science hiring managers have no or limited practical experience with doing actual Analytic work so they get overly focused on paper qualifications and buzzwords. This is reinforced by HR people who love buzzword bingo.

[fbmac]

I created a vehicle plate recognition system before ML got cool, but I can't get any ML job with my less than bachelor degree (associate? dunno how to translate) here in Brazil. I think there are only 2 positions open for machine learning less than 100km from where I live.

I feel left out.

[compcoffee]

>As someone who has been producing value in a data science/machine learning role for multiple years, it's disheartening to see comments that I may be blacklisted from positions due to "only" having a bachelor's degree.

Don't worry.

The big salaries will go to people who create value and solve problems. You can do that without a PhD. In fact, if most Data Science communities are representative, PhDs feel they're above 90% of the work required to put data to work to solve problems. You know, the ones who walk into a job and say, "Oh, I don't get to apply the latest algorithm onto a perfectly cleaned toy data set? I'm leaving!". They're going to have their lunch eaten.

[prestonh]

I come from the background you describe, have lots of friends from the same background, and my experience has been the opposite. Most people know that data is messy business and that as data scientists we will often serve more as engineers in our day to day work.

[citation_please]

Hah. I want to feel this is right. I like to think of my work as the "full-stack" equivalent of the "data science" career path. There's no part of the data pipeline I'm not currently doing/qualifed to do/interested in doing: acquisition, transformation, storage, exploration, analysis, machine learning, presentation & dashboarding, integration, server maintenance & operations...

The "toy examples" require only a very small subset of the skills required to extract business value from an amorphous blob of data.