How Many Data Scientists are There and is There a Shortage?

Recently saw this article on KDnuggets (check them out if you aren’t already subscribed) and thought it was worth using to update some of my slides about the current talent shortage for Data Science & Analytics (DSA) skills.

This shortage is definitely acute here in the Philippines.

The 2011 McKinsey report on Big Data said that “The United States alone faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of Big Data.”


In 2014, KDnuggets examined “How Many Data Scientists are out there?” and came with an estimate of 50-100,000, and did not see much evidence of a massive shortage then. In 2014, we found only about 1,000 job ads for “Data Scientist” on indeed.com. 


Now that we reached 2018, KDnuggets has examined how accurate were those predictions and tried to answer three questions:

1. Is there a shortage of Data Scientists now?
2. How many “Data Scientists” are there , both in name and in function ?
3. What are the future prospects for Data Scientists?

 

The answer to the first question is a resounding YES!
  • LinkedIn Workforce Report for US (August 2018) says “Demand for data scientists is off the charts  … data science skills shortages are present in almost every large U.S. city. Nationally, we have a shortage of 151,717 people with data science skills.
  • Note that LinkedIn reports shortages for people with “Data Science Skills”, not necessarily people with “Data Scientist” title.
  • We can estimate the demand for “Data Scientists” from two popular job search sites – indeed and Glassdoor.
  • Search on indeed.com for “data scientist” (in quotes) in USA finds only about 4,800 jobs. However, in a search for data scientist without quotes, about 30,000 jobs.
US is the largest but not the only market for Data Scientists. We can also see strong demand for Data Scientists elsewhere:
  • UK: 1,100 jobs
  • Germany: 900 jobs
  • France: 718 jobs
  • Philippines: 599 jobs  — You Read That Right! More than India.
  • India: 500 jobs
Glassdoor search for “Data Scientist” finds about 26,000 jobs in USA (same results if quotes are removed).
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Question 2: How Many “Data Scientists” are There, Both in Name and in Function?

Google search defines a data scientist as “a person employed to analyze and interpret complex digital data, such as the usage statistics of a website, especially in order to assist a business in its decision-making.”

There are many people in the industry and academia who do this work without having the formal title of a data scientist, since Data Science is an interdisciplinary field at the intersection of Statistics, Computer Science, Machine Learning, and Business. We can estimate the current population of Data Scientist by examining popular data science platforms.

Kaggle (now part of Google) is a platform for data science  and analytics competitions. It claims to be the world’s largest community of active data scientists.

While not all Data Scientists take part in Kaggle competitions or have a Kaggle account, and not all Kagglersdo work of data science, it is reasonable to assume a large overlap.

On Sep 19, 2018 Kaggle says they surpassed 2 million members in August 2018.

Since not all Kaggle members are active, Kaggle membership is probably a global upper bound for people engaged in data science.

KDnuggets is now reaching over 500,000 unique visitors per month.

KDnuggets now has about 240,000 subscribers/followers over Twitter, LinkedIn, Facebook, RSS, and email.

On LinkedIn, there are many groups dedicated to data science, and although the engagement in those groups has been falling, we can use their membership as a rough estimate. Here are three of the largest groups

  • Big Data and Analytics  –  339,000
  • Data Science Central – 278,000
  • Data Mining, Statistics, Big Data, Data Visualization, and Data Science – 170,000

Searching LinkedIn for “data scientist”  (quotes are important) we find over 100,000 people with that actual title.  So if globally between 200,000 and 1,000,000 people are doing some Data Science related work, then a majority of them does not have a Data Scientist title.

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We can also estimate the by looking at activities related to languages and platforms most connected to Data Science: R, Python, Machine Learning libraries, Spark, and Jupyter.

  • Apache Spark Meetups had 225K members recently and growing every month.
  • Intel Capital estimated that there 1 million R programmers worldwide.
  • Based on the public data on python.orgwebsite, there have been around 2.75 million downloads.
  • Jupyterproject has around 3 million users at present.

These numbers can give us a rough upper limit on the number of data analysts/data scientists around the world.

So yeah, to answer the question, there are at least 200,000

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Question 3: What are the Future Prospects for Data Scientists?

The near-term future for Data Scientists looks bright.

LinkedIn 2017 emerging jobs report claims that machine learning engineers working today has increased by 9.8 times as compared to 5 years ago.

Machine Learning Engineers, Data Scientists, and Big Data Engineers rank among the top emerging jobs on LinkedIn. Data scientist roles have grown over 650% since 2012.

Job growth in the next decade is expected to outstrip growth during the previous decade, creating 11.5M jobs in the Data Science/Analytics area by 2026, according to the U.S. Bureau of Labor Statistics.

IBM recently claimed that by 2020 the number of Data Science and Analytics job listings is projected to grow by nearly 364,000 listings to approximately 2,720,000. No matter what the true number of data professionals out there currently, their number is likely to grow in the near future.

So What are the Future Prospects for Data Scientists in the Philippines?

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Based on Data from APEC (Asia Pacific Economic Cooperation), there is both a huge demand here in the Philippines as well as in the jobs where the Philippines already has an outsourcing pipeline too.

SO what does that mean for you?

You Need to Know Exactly What You Need to Hire/Learn how to have/be a Data Scientist?

And it’s not easy.

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To assemble a team of DSA Practitioners, you need to make sure you have the right combination of talent.

Here is how I would start.

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Make sure you have people who can do these functions.

And if you want to learn how to be one of these key players, I’m betting you need to know where to start.

So wether you want to be a DSA enabled professional or you want to assemble a DSA team, here is a better understanding of how that looks.

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Yeah I know. It is a lot!

So, what now?

Connect with DMAIPH and we will get you started!

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DMAIPH – Decision-making, Analytics & Intelligence Philppines

Over the past few years businesses in the Philippines have invested heavily in big data, analytics and data science, but still have not achieved the expected outcomes of data-driven companies.

Based on our learnings from the 100’s of Filipino businesses and 10,000s of Filipinos who have taken part in DMAIPH Analytics trainings all across the country, we have crafted a proven,  non-technical approach to upskilling your team in analytics.

In 2019, we will be launching two new training programs: (1) Our DMAIPH Applied Analytics Master Class series for executives, leaders and decision-makers and our (2) DMAIPH Applied Analytics Boot Camp series for practicing analysts.

We will feature case studies of real Filipino run business, exercises based on actual analytics challenges being solved by Filipino analysts, and provide you with a copy of my book, Putting Your Data to Work, an analytics guidebook for the Filipino professional

Connect with us via our marketing partner, http://www.sonicanalytics.com to learn about upcoming analytics trainings and events. 

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HR & Recruitment Analytics: Win The Talent War (Mar 28 in Ortigas)

Updated 11/19/16

It’s pretty clear to anyone who is paying attention that the current talent acquisition challenges facing BPO’s in the Philippines is getting worse at an alarming pace.

This trend is echoed across the planet as we have had a global failure in approaches to preparing the youth for the careers we need them to fill. There are several initiative underway in the Philippines to address this, but at this point its just a drop in the bucket when you look at the projections for talent with analytics skills, management potential and a strong work ethic.

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Check out our next training on March 14 in Ortigas. Here is the link >>>

I recently came across this post on LinkedIn that outlined 5 things that we need to work together to do to make sure the generation hitting the workforce now and especially the generation now in school, ready for prime time.

The talent shortage is particularly serious at the middle-management level as companies dither over how to develop high-potential entry-level employees into more senior roles within their organisations.

Solving it requires planning for the long-term and building a talent investment strategy into the corporate culture, which suggests that solving the talent shortage calls for new thinking, new approaches, and collaboration on an industry-wide scale.

Relying on the traditional education path – universities – to fill the talent needs won’t work because that will take years. We a faster solution – one that combines a multi-pronged approach, and one that is collaborative across all players in the business.

The article concludes with five ways of helping to solve the talent crisis threatening companies small and large all across the globe.

  1. Industry collaboration: Industry leaders joining forces to work with universities, colleges and trade associations to develop specific education programs to fill the expected openings.
  2. Expanded in-house and external education options: A growing number of firms are developing their own education programs making full use of senior existing internal expertise.
  3. Job rotation programs: A ‘talent exchange’ rotation to promote cross-functional development, which would also keep employee interest.
  4. Formalised knowledge transfer: Capturing people’s knowledge before it “literally walks out of the door” into retirement.
  5. Becoming an employer of choice: Taking steps to ensure that the company is an attractive place to work by providing competitive salaries linked to a valued career path.

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DMAIPH can help you by consulting with your management team on how to get ahead of the curve, by providing training to your team on how to optimize your talent acquisition an retention programs and/or by providing you with talent to fill your open positions.

HR & Recruitment Analytics – The recruitment and retention of top talent is the biggest challenge facing just about every organization. You really have to Think Through The Box to come up with winning solutions to effectively attract, retain and manage talent in the Philippines today.

DMAIPH is a leading expert in empowering HR & Recruitment teams with analytics techniques to optimize their talent acquisition and management processes. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to learn how to get more analytics in your HR & Recruitment process so you can rise to the top in the ever quickening demand for top talent.

HR Predictive Analytics is the Next Big Thing in Talent Management (Mar 28 in Ortigas)

Predictive analytics are a rapidly upcoming trend in Human Resources.

Even though a lot of people talk about predictive analytics in HR, hardly any organizations are really able to tie success in HR with success to the bottom line. By applying predictive analytics to business data, HR should be able to add value as a strategic partner that relies on proven and data-driven predictive models, instead of relying on gut feeling and soft science.

Last year, Towers Watson found that one in three organizations planned to increase spend on their HR function by more than 20 percent, and HR data and analytics tools rated as one of the top areas for investment.

However, just looking at HR data in isolation does not represent the best opportunity to make an impact. In fact organizations today need to be able to use predictive analytics for a wide range of functions, especially to:

  1. Measure employee engagement and workforce perceptions
  2. Predict employee turnover
  3. Predict employee performance
  4. Monitor impact of business interventions

This learning session is specifically designed to provide HR teams with a strategic road map to bring together all the relevant data in a business and to use it to predict successful outcomes. Join us March 14, 2017 in Ortigas. HR Predictive Analytics is just one of the topics we will discuss. Click here for more info >>>

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HR & Recruitment Analytics – The recruitment and retention of top talent is the biggest challenge facing just about every organization. You really have to Think Through The Box to come up with winning solutions to effectively attract, retain and manage talent in the Philippines today.

DMAIPH is a leading expert in empowering HR & Recruitment teams with analytics techniques to optimize their talent acquisition and management processes. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to learn how to get more analytics in your HR & Recruitment process so you can rise to the top in the ever quickening demand for top talent.

Creative Ways to Access Big Data Talent

http://www.forbes.com/sites/bernardmarr/2016/09/16/5-creative-ways-to-access-big-data-talent/#6baf4eec580c

Came across this blog post and thought I worth sharing and talking about.

“Demand for big data expertise is growing every day, as more and more companies become aware of the benefits of collecting and analyzing data.”

Just take a look at jobs boards now and from postings a year ago. You can see the number of jobs with analyst or data scientist in them grow like crazy.

“Unfortunately, the number of people trained to analyze this data isn’t growing in line with the demand.”

It shouldn’t be too hard to start guessing at the total number of data geeks needed in today’s global economy. For the sake of argument, if you figure every company with at least 100 employees needs someone to handle internal analytics and every company with at least 1000 customers’ needs someone to handle external analytics… it’s a mindboggling number.

“This creates a challenge for companies looking to hire expert people, especially for smaller firms less able to compete on salary and benefits.”

Not only can big companies invest in top analytics talent, they can also use business Intelligence tools, AI and machine learning to automate data jobs. Smaller companies are not only competing for talent, they are up against huge technology hurdles as well.

“The good news is that, even if you’re having trouble recruiting data scientists because of stiff competition, or if you simply haven’t got the budget to recruit, you can still access big data skills.”

And that is what I agree with 100%. You have to get creative. Going outside to hire someone to come in and manage your data and analytics, to be a data scientist, you are forgetting one key thing. To make use of all the technology out there and to be able to really get value out of analytics techniques, you need to understand the needs of the business.

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In the end, what makes a business analyst, data scientist or big data expert successful has nothing to do with how well they can code, build models or blend data. It has to do first and foremost with can they understand the business in ways to put their big brains to work to solve problems and answer questions relevant to the business.

That is the dilemma. You need people on the inside who know the business, but you can’t get a data super hero to come work for you.

To that end here are my 5 ways to get the most out of your data talent without going outside to hire.

  1. Promote and empower your own data geeks.
  2. Send your team outside to get training from a pro.
  3. Bring in an expert as a consultant and mentor your team.
  4. Get intern/OJT help from local colleges to bring in new perspectives.
  5. Outsource some of your data initiatives to experts and learn from them.

With each of these options, there are significant challenges. As I said before, the best solutions is finding someone with business acumen that pertains to your business.

I will go into more detail with each of these options over the next few blog posts.

 

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Promote Your Own Data Geeks

 

 

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Get Trained By the Analytics Pros

 

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Find Your Team A Mentor

 

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Infuse Your Business with Fresh Analytics Talent

 

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Outsourcing Analytics To Experts Is Not A One Way Street

Recruitment Analytics: A Simple Classification System

How do you classify the applicants in your pipe line? There are hundreds of ways to separate resumes at the first point of contact by potential job fit. Most Applicant Tracking Tools have this built in and really smart ones will auto separate and classify based on keyword searches.

If you can afford an ATS or have veteran recruiters and/or an optimized process you are probably already doing this. But you would also be shocked to know how many companies are not doing this.

To get started just create 3-4 piles to put resumes in. Its as simple as this:

  • Pool A is for candidates who have most if not all of the qualifications you are looking for.
  • Pool B is for applicants who have some of the qualities.
  • Pool C is for applicants who really don’t have any of the things you are looking for and/or have some fatal flaws that you believe are incompatible with the job.
  • Pool D can be for resumes who currently don fit, but might in the future.

If you are just using Excel to track your applicant pipe line, it is easy to add a column for general classification. Through in some weighted scoring to rank within each category and you are actually doing better than a lot of small and medium sized companies.

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Just as an example, In each pool, you can add a rank of High, Medium and Low. High being they should be ready to start day one, medium meaning the will need some training time if they are hired and low meaning they will need some extensive training.

It is really that simple. Starting adding structure to your recruiting so you can focus your time and energy on those who have the most potential to help you right now, but also keep track of those who might be able to help you down the road.

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If you don’t have a good ATS, then doing something like this will make a huge difference. You will soon be able to start making more strategic choices on who you spend your time, focus and money on.

HR & Recruitment Analytics – The recruitment and retention of top talent is the biggest challenge facing just about every organization. DMAIPH is a leading expert in empowering HR & Recruitment teams with analytics techniques to optimize their talent acquisition and management processes. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to learn how to get more analytics in your HR & Recruitment process so you can rise to the top in the ever quickening demand for top talent.