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Sorry, but you need a Masters degree to be a Data Scientist

You want to be a Data Scientist, and you’ve read that you might not actually need a Masters degree or even a PhD to get the job of your dreams. Let me guess? You’ve been told by this by various ‘experts’, and now you have some doubts.

First of all, there are some major sceptics out there who probably aren’t actually Data Scientists. Yep, we know about them, and we know better. You want the truth? You need a Masters degree and/or PhD to get a fulfilling, progressive and well-paid career in Data Science.

The idea of completing a bunch of online courses and MOOC’s then landing a six-figure position without a Masters is possible but improbable. Particularly in Australia, where a Masters is essential to getting a legitimate role with career progression and skill development. And unlike the US, PhDs are very very valuable.

“You need a Masters degree or PhD to get a fulfilling, progressive and well-paid career in Data Science.”

– Legitimately every Data Scientist

Something to remember is that the ‘field ‘is relatively new. Stories of people who have managed to build up their skills and now have a fantastic career in Data Science are often people who finished their Computer Science, Mathematics or Statistics related bachelors 8+ years ago. They have been able to transition into these roles as the position became more defined. These people are driven and are continually honing their skills through online courses, Kaggle competitions and seeking out skill development opportunities.

As the field developed more post-graduate degrees were marketed for Data Science. The first batches of graduates entered the Australian job market in 2017. Since then employers have come to expect a Masters degree in Data Science because there are so many people with that qualification, and the number is rising.
It is possible to get a job in Data Science without a post-graduate degree, but you have to be lucky, connected or a genius math nerd with pro-hacking skills. Now be honest with yourself, is that you?

Before we look into the job market, let’s address a significant motivator in why people do a Masters, money.

Data Science degrees are expensive. Really expensive. The average cost of a 2 year Master of Data Science in Australia is $65,000 for a domestic student and $80,000 for an international student. It’s a considerable investment, especially if you are already $45,000 in debt from your undergraduate degree. But the good news is that salaries for Post-graduates are pretty competitive. The Graduate Outcomes Survey statistics back this up. 

With an undergraduate degree in Computer Science or Information Systems, you can expect a median graduate salary of $60,000 pa. For Post-graduate that jumps to $96,000 pa. That’s a 60% increase! Graduates with a Bachelor in Science, by comparison, can expect a median graduate salary of $63,000, rising to $78,300 for those holding a post-graduate degree. The average full-time Australian wage is $82,500 in June 2018.

Comp.Sci and Info. System 2018 undergrad salary $60,000

Comp.Sci and Info. System 2018 postgrad salary $96,000

– 2018 Australian Graduate Outcome Survey

These numbers are compelling. Clearly, a post-graduate degree is valuable to employers.

To get a good overview of the Australian Data Science job market, we hopped on to search for jobs with the title ‘Data Scientist’ which returned 262 jobs. Breaking them up into pay bands, we start to get an understanding of the Data Science job market and why people say ‘you don’t need a Masters’.

The $50,000 – $60,000 pay band

Setting the pay band filter to reflect the low end of the median undergraduate salary, we immediately see a few scary trends.

Some recruiters are opportunistic

Reading these ads, the wise words of Darryl Kerrigan come to mind

“Experienced Data Scientist for 50-60k? Tell’em they’re dreaming”

– Darryl Kerrigan if he was a Data Scientist

For example, this is a job advertised for the Australian Federal Government, but it is more likely for a contractor. This job is a classic example of ridiculous opportunistic recruiters trying to rip off legitimate postings for senior roles. Ignore and don’t look at these recruiters again.

A job that is advertised for a ‘Data Scientist’ isn’t always for a Data Scientist

Unfortunately, with the hype around Big Data, companies and recruiters have taken to using the title a little too liberally. It might be disheartening to see jobs advertised as low as $50-60k, but in reality, these jobs will be meant for graduates of a business or commerce bachelors degree. If you took these jobs, you will likely be using proprietary tools and do little development work.

The $60,000 – $90,000 pay band

When we increase the pay band to get more legitimate roles. But there aren’t many. On first glance, people will look at this and see 12 Data Science jobs. But is there?

The liberal use of ‘Data Scientist’ is evident again. Out of the 12 that were returned we got :

2 x Junior Data Scientist/Data Analysts

1 x Digital Analyst

2 x Junior Software Engineers

1 x Junior Campaign Analyst

1 x Procurement Specialist

3 x Data Scientists

1 x Junior Data Scientist

We excluded the Junior Software Engineer and Procurement specialist roles, they are not relevant. The two Junior Data Scientist/Data Analyst, Junior Campaign Analyst, Digital Analyst and the Consultant/BI and Analytics jobs fall into the example of those meant for business or commerce undergrads. In fact, it even says:

“Degree with a strong quantitive focus such as; statistics, physics, psychology, economics or commerce”

– Badly targeted job ad

Little room to learn skills in Machine Learning, Programming and Workflow Development

These types of job posts list SAS and other proprietary software experience as a requirement. They don’t tend to require you to program in a broad range of languages or actually plan your own analyses. It is unlikely these jobs will set you up for hardcore Machine Learning and AI development roles in the future. Click on the image to read a few.

Some companies go fishing for a Masters without mentioning a Masters

Some companies will specify a specific type of undergraduate degree and also ask for a minimum of 2 to 3 years experience with Python, Scala, Spark or similar. These roles are almost impossible to get unless you have been working in the industry and since it is hard to get a role where you are actually developing these skills as an undergraduate (e.g. this role), your best bet is a Masters or higher to compensate. These types of recruiters are casting the net wide but know what they want, and they want it cheap.

From here, the remaining three positions for a Data Scientists are offered at $80,000 pa. All want a PhD or Master’s degree.

The $90,000 – $130,000 pay band

The Masters-Experience tradeoff

Moving up, we see 85% of the ads specify a required PhD or Masters, often with 2-8 years of experience tacked on for good measure. Think of it like a trade-off, a PhD with no industry experience already has 3 years working on a project with real deadlines, often with industry partners. A Masters student will be doing projects throughout the 2 years, and a lot of them have scored data analyst roles part-time throughout their degree based on their undergrad skills. Undergrads are unlikely to have that opportunity. 

Don’t be fooled by the words ‘preferred’ and ‘or’. ‘Prefered’ means ‘must’. The market is flooded with Masters graduates who have an advantage over undergrads. Unless you have 3 years of project management experience and some serious skills, then you can’t compete. Remember, HR and recruiters run the show, not the team you will work with. Here are some examples.

PhDs are valued in Australia

Actually, some recruiters are getting desperate for them. Unlike the American rhetoric that is generated from the post GFC job crash, a PhD will put you in good stead in Australia for a career in Data Science. It’s just a hard route to go. But clearly they are getting desperate and it’s kind of awkward.

The $130,000 + Pay Band

These roles are difficult to get, but there is a big demand for them, mainly because they require business acumen and consulting experience. However, we still see some odd marketing tactics with interesting use of emojis. This one is on for $150,000 pa.

“If you are a Data Scientist who could also walk into a high performing Senior Insights role with a Consulting firm (eg, presentation skills, customer engagement, strategy and planning, insights to find opportunities,  drive sales etc.) then stop what you are doing and send me your CV !- I need to speak with you immediately :-)”

– Desperado

In fact, some are even asking for journal publications.

Have you published?

I love reading this. As someone with a Masters in Data Science, now doing a PhD in Text Analytics and Organisational Performance Analytics, I know I have a good pay packet waiting for me if I choose to step away from academia.

So with that, I hope you now have a better idea of the Australian job market for Data Scientists and why the following articles (from the USA) are bull.

Cleverism – 4 Reasons Not To Get That Masters in Data Science

Forbes – You Can Get A Data Analytics Job Without A Masters In Data Science

Topbots – You Don’t Need a PhD to Master Machine Learning & Data Science

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