Powerful Lessons From a Passive Job Seeker

Do you ever wonder how some people just seem to attract all the “plum” opportunities? Well today, I am going to pull back the curtain on just how these people attract the right opportunities.

Howie Schnuer, CMO and Vice President/General Manager, Small & Medium Enterprises at TSI
Howie Schnuer, CMO and Vice President/General Manager, Small & Medium Enterprises at TSI

Do you ever wonder how some people just seem to attract all the “plum” opportunities? Well today, I am going to pull back the curtain on just how these people attract the right opportunities.

I sat down with my colleague, Howie Schnuer, CMO and Vice President/General Manager, Small & Medium Enterprises at TSI, to talk about how he landed his most recent position.

In Howie’s words, he says he’s just been lucky in combination with making the right choices. I say he’s been lucky by design. Let me know what you think after you read an edited version of our conversation:

Michelle Robin: How did you find out about this opportunity?

Howie Schnuer: Prior to this role, I was at Infogroup heading up the marketing for the small and medium business division. And I was happy, content, and comfortable. Then I got an email from a recruiter about this position, which did look interesting. But as I said, I was really happy so I hit the delete button. Next, I got another email from the recruiter, and another and another. So by the fourth or fifth email I said, okay, let’s talk.

Robin: So what do you think made the recruiter keep pursuing you?

Schnuer: I suppose he liked how my career progressed. I had kept moving up and also had a lot of variety in my experience. I wasn’t just doing one type of marketing or one type of sales. I had worked in big corporations like W.W. Grainger and small startups like Restaurant.com.

Robin: Since you weren’t actively looking for a job at the time, did you even have an updated resume?

Schnuer: Funny you ask. It wasn’t updated for presentation, but that is actually one of the things I always do. I keep bullet points of what I have recently accomplished so I have the notes right there when it comes time to update it. I would love to have had the time to have it professionally done, but this wasn’t one of those times.

Robin: And then how did you decide this was going to be the right move for you?

Schnuer: That was the hard part because I was at a job I truly enjoyed. In the end, it came down to being a really good match of my experience and what they were looking for. It was an opportunity for me to just focus on building a sales channel and enhancing the sales operations division, initially, and that was exciting. Plus, it didn’t hurt that it was going to be a 15-minute commute versus working from home and traveling a lot.

Robin: Once you started, what did you do to ensure you made an immediate impact on the business?

Schnuer: You know, I had never done a true 90-day plan before this role, but when I got here that is exactly what I did. I just dug in and saw a lot of low-hanging fruit. After 30 days I started digging deeper, created new objectives and focused on getting results. My team is really great and today we are continuing to do the same thing, digging in and making things happen.

Robin: Your original role expanded to include CMO duties after only six months. How did that happen?

Schnuer: Like I just mentioned my team and I started seeing some initial results pretty fast. The positive movement was something they had not seen in quite some time in the SME division. The CEO who I interviewed with and continued to have regular interactions with approached me and said this opportunity is available, would you be interested? Of course, I said yes. And because they were seeing such great results they wanted me to continue in my current role and also take on the CMO role.

Robin: Okay, so what advice do you have for marketing professionals embarking on an executive-level search? Do you think it differs from looking for any other role?

Schnuer: That’s a tough question to answer for me, because I didn’t embark. It just kind of happened.

But, I think one thing that is really important is to always have a great network. A network that you can pick up the phone and call with a question or ask for support. It’s important because a lot of jobs will come out of this – ones that are not even posted, the hidden job market.

6 Strategies to Land a New Job By January 

With Halloween gone and Thanksgiving just around the corner, you can easily get distracted by all the festivities and put your job hunt on hold. It’s actually a common misconception that hiring doesn’t happen over the holidays. In reality, it couldn’t be further from the truth.

Find a New Job by JanuaryWith Halloween gone and Thanksgiving just around the corner, you can easily get distracted by all the festivities and put your hunt for a new job on hold. It’s actually a common misconception that hiring doesn’t happen over the holidays. In reality, it couldn’t be further from the truth.

Last year I delivered documents for a client on November 23 and by early January, he started a new 6-figure job. The year prior, I bumped into a client in November who had been in transition for several months. I told her to not slow down her search over the holidays. She emailed me in early January to say she was starting a new position.

Hiring does happen over the holidays. Here are six ways to make the most out of the holiday season for your job hunt.

1. Ramp up Your Job Search During the Holidays

Most of your peers slow down their search because they think that “people are busy”, or “no one is in the office.” So that means there is less competition out there for you. The last quarter of the year is actually pretty active. In fact, according to the U.S. Bureau of Labor Statistics, the hire rate for December 2015 was more than 5 percent higher than in January 2016. Oftentimes, companies have head counts that they will loose if they don’t fill it by year-end. Or they know they are getting approval to hire in January so they start searching now in order to have the new person starting in early January.

2. Re-engage Your Network With Holiday Greetings

The holidays are a perfect time to reconnect with your network — recruiters, colleagues and previous employers — and provide a reminder that you exist. It’s as easy as dropping them a note on LinkedIn, or arranging a time to meet and catch up.

3. Work the Room at Holiday Parties

Social events are pretty synonymous with the holidays. Not just family events, but events at work and any associations you may be a part of. No one is expecting you to be fishing for job leads at one of these events, so it’s easier to keep things more casual. But people feel more giving around the holidays and want to help.

If parties usually make you feel like running the opposite direction, seek out the other person standing alone and engage in some small talk. Ask some questions about their holiday traditions or their favorite thing to do over the holidays. Eventually the conversation naturally leads to, “So what do you do?” This is when you can mention your career goals or that you are looking for a new challenge.

4. Reach Out to ThirdParty Recruiters 

Lack of open positions is not the challenge for recruiters during this time of year — in fact, the challenge is in the pool of candidates drying up. Recruiters are motivated to fill any open positions by year-end so they can earn their commission. So make third-party recruiters be your secret weapon to snag an offer and have a great reason to celebrate on New Year’s Eve.

5. Be Flexible

Those involved in the hiring process may be trying to take some vacation time themselves. So if you can make yourself available you’ll likely have an advantage over your competition. This may mean you need to be willing to come back early from vacation or shift holiday plans. There is no reason to go extreme and cancel without an interview secured, though. That will just disappoint you and your family.

6. Update Your Personal Marketing Materials

Finding time to job search while you’re employed is not always easy. Make the most out of your time off and get your resume, LinkedIn profile and cover letter up-to-date. Gather your reviews and make notes about the projects you’ve completed over the last 12 months. Ask your colleagues for recommendations on LinkedIn. Better yet, gift your colleagues and former managers by writing a recommendation for them, first.

It truly is the most wonderful time of the year to be in job search! Companies don’t stop hiring just because it’s the holidays. Happy job hunting!

What’s Next for Marketing Careers in Digital and Multichannel? 

It’s not too early to start thinking about what is ahead for your career with 2017 quickly approaching. What skills should you improve? How can you make yourself more appealing to potential employers, or position yourself for a promotion? To provide you with some direction, I recently spoke to executive digital and multichannel recruiting expert, Jerry Bernhart.

Jerry Bernhart, Principal of Bernhart Associates Executive Search, LLC
Jerry Bernhart, Principal of Bernhart Associates Executive Search, LLC

It’s not too early to start thinking about what is ahead for your marketing career with 2017 quickly approaching. What skills should you improve? How can you make yourself more appealing to potential employers, or position yourself for a promotion?

To provide you with some direction, I recently spoke to executive digital and multichannel recruiting expert, Jerry Bernhart. As principal of Bernhart Associates Executive Search, LLC, Jerry has conducted searches as well as recruited and placed top digital and multichannel marketers, with clients ranging from startups to Fortune 500 companies, for more than 20 years.

Here is an edited transcript of our conversation.

Michelle Robin: How different is searching for a job today than say just two years ago?

Jerry Bernhart: Two years isn’t a lot of time. There hasn’t been a dramatic amount of difference, particularly since the recession. But I can give you some examples of what is going on in the industry today.

Right now, I am wrapping up a recent search for a manager of e-commerce — a really hot segment. When this search started two months ago, I surfaced eight to ten candidates, and I lost half of them in the first four weeks because my client couldn’t move quickly enough. This shows an enormous demand for this type of person.

With another search for a CRM (customer relationship management) manager, I had candidate who ended up with four external offers plus a counter offer. For best-of-breed talent, this is what I am seeing happen often.

Robin: What is your number one tip for job seekers looking to get ahead in their marketing career?

Bernhart: Keep learning. The beauty of digital is it makes it so easy to learn online. There is so much out there and things are moving so quickly, it’s essential to stay on top of things. The day you quit learning is the day you need to quit marketing.

If I could add another thing, I would say to be open regarding location. If you’re not living in a top metro area, look at other places. There are a lot of opportunities out there and you may not find them in your own hometown because you are in a smaller market. It’s kind of like broadcasting. The top news anchors didn’t start in New York City. So for young professionals especially, go to where the opportunities are and expand your scope of knowledge and responsibilities. Do it in small steps though, so you don’t take a big hit on the cost of living.

Robin: How important is your online brand for digital marketing professionals? Do employers actually look at your personal website, social media profiles, etc.?

Bernhart: It’s critical! You should think about your personal and online brand as often as you get your haircut. Think about it, you don’t know how long you’re going to be working at your current employer. You can’t afford to ignore your brand. If you don’t know how to brand yourself, how can you brand an organization?

The first thing human resources people do, even more than hiring managers, is Google you and look you up on LinkedIn. They may have your résumés, but the problem with résumés is you can’t always believe what is on there. So, put your personal URL on your résumé.

I have lots of candidates who have side projects. You can use that as the perfect opportunity to show a potential employer what is going on. I’ve never seen it have a negative impact on someone’s candidacy. In fact, I prefer they are upfront and transparent about it. 

Golden Nuggets: Advertising’s ‘Data’ Wave Has Arrived

When I look at the world of advertising, by way of my career path through the Direct Marketing Association and Harte Hanks and now with the Digital Advertising Alliance—I confess I’ve been a “direct response” snob by training. (As a PR guy, I tend to enjoy Kool-Aid.)

When I look at the world of advertising, by way of my career path through the Direct Marketing Association and Harte Hanks and now with the Digital Advertising Alliance—I confess I’ve been a “direct response” snob by training. (As a PR guy, I tend to enjoy Kool-Aid.)

Always a victim of brand czars and image advertising, the world of direct response long has been relegated to “below the line” and ironically “unmeasured media”—even though direct-response marketers (no matter what the medium) always had the secret sauce in sight: relentless testing, true measurability and accountability, all to figure out which advertising messages and campaigns actually produced. The result might be a sale, a lead, traffic—always a defined objective, with a return on investment obsession. What’s not sexy about advertising that works?

It seems like for 20-plus years—with the rise of database marketing, customer relationship management, inbound marketing, agency holding companies gobbling up digital and direct agencies, marketing automation, customer centricity, brand interaction, personas and analytics—we might be able to say to ourselves, data-driven advertising has arrived! All marketing is now integrated! We are now welcomed in the C-suite!

That does not take anything away from brilliant creative—we all love brilliant creative—but if the offer, the strategy, the audience are not on target, what good is brilliant creative?

Recently at the Direct Marketing Club of New York January luncheon, Bruce Biegel, senior managing director, The Winterberry Group, presented his annual media roundup of the prior year with projections for 2015. As Targeting Marketing reported, it’s a data lover’s dream. Every trend behind follow-the-money seems to point to responsible data collection, data sharing and data use at its core.

Bruce didn’t hold back. Direct and digital spending is forecast to grow 7.3 percent this year—compared to 1.5 percent growth for measured media (image advertising) categories. The former will feed GDP growth, he forecasts, while the latter will lag.

This is not a rub-your-face-in-it post (I’ve been on the other side a few times, too). It’s simply a recognition that whatever our biases and opinions about what’s hot and what’s not on Madison Avenue, Silicon Valley and data centers everywhere, it’s that advertising technology, the data sharing that fuels such technology, and the strategic insights and marketing executions made possible by analytics, are now a top priority for most every Chief Marketing Officer. DMA and even The White House previously have documented these trends.

We’re in the limelight—as much as digital and now data disruption has been uncomfortable for many, and with so many data silos still to break through and smart people yet to hire to make sense of it all. Ladies and gentleman, the glow feels good.

Happy Data Innovation Day this week (January 22).

How to Be a Good Data Scientist

I guess no one wants to be a plain “Analyst” anymore; now “Data Scientist” is the title of the day. Then again, I never thought that there was anything wrong with titles like “Secretary,” “Stewardess” or “Janitor,” either. But somehow, someone decided “Administrative Assistant” should replace “Secretary” completely, and that someone was very successful in that endeavor. So much so that, people actually get offended when they are called “Secretaries.” The same goes for “Flight Attendants.” If you want an extra bag of peanuts or the whole can of soda with ice on the side, do not dare to call any service personnel by the outdated title. The verdict is still out for the title “Janitor,” as it could be replaced by “Custodial Engineer,” “Sanitary Engineer,” “Maintenance Technician,” or anything that gives an impression that the job requirement includes a degree in engineering. No matter. When the inflation-adjusted income of salaried workers is decreasing, I guess the number of words in the job title should go up instead. Something’s got to give, right?

I guess no one wants to be a plain “Analyst” anymore; now “Data Scientist” is the title of the day. Then again, I never thought that there was anything wrong with titles like “Secretary,” “Stewardess” or “Janitor,” either. But somehow, someone decided “Administrative Assistant” should replace “Secretary” completely, and that someone was very successful in that endeavor. So much so that, people actually get offended when they are called “Secretaries.” The same goes for “Flight Attendants.” If you want an extra bag of peanuts or the whole can of soda with ice on the side, do not dare to call any service personnel by the outdated title. The verdict is still out for the title “Janitor,” as it could be replaced by “Custodial Engineer,” “Sanitary Engineer,” “Maintenance Technician,” or anything that gives an impression that the job requirement includes a degree in engineering. No matter. When the inflation-adjusted income of salaried workers is decreasing, I guess the number of words in the job title should go up instead. Something’s got to give, right?

Please do not ask me to be politically correct here. As an openly Asian person in America, I am not even sure why I should be offended when someone addresses me as an “Oriental.” Someone explained it to me a long time ago. The word is reserved for “things,” not for people. OK, then. I will be offended when someone knowingly addresses me as an Oriental, now that the memo has been out for a while. So, do me this favor and do not call me an Oriental (at least in front of my face), and I promise that I will not call anyone an “Occidental” in return.

In any case, anyone who touches data for living now wants to be called a Data Scientist. Well, the title is longer than one word, and that is a good start. Did anyone get a raise along with that title inflation? I highly doubt it. But I’ve noticed the qualifications got much longer and more complicated.

I have seen some job requirements for data scientists that call for “all” of the following qualifications:

  • A master’s degree in statistics or mathematics; able to build statistical models proficiently using R or SAS
  • Strong analytical and storytelling skills
  • Hands-on knowledge in technologies such as Hadoop, Java, Python, C++, NoSQL, etc., being able to manipulate the data any which way, independently
  • Deep knowledge in ETL (extract, transform and load) to handle data from all sources
  • Proven experience in data modeling and database design
  • Data visualization skills using whatever tools that are considered to be cool this month
  • Deep business/industry/domain knowledge
  • Superb written and verbal communication skills, being able to explain complex technical concepts in plain English
  • Etc. etc…

I actually cut this list short, as it is already becoming ridiculous. I just want to see the face of a recruiter who got the order to find super-duper candidates based on this list—at the same salary level as a Senior Statistician (another fine title). Heck, while we’re at it, why don’t we add that the candidate must look like Brad Pitt and be able to tap-dance, too? The long and the short of it is maybe some executive wanted to hire just “1” data scientist with all these skillsets, hoping to God that this mad scientist will be able to make sense out of mounds of unstructured and unorganized data all on her own, and provide business answers without even knowing what the question was in the first place.

Over the years, I have worked with many statisticians, analysts and programmers (notice that they are all one-word titles), dealing with large, small, clean, dirty and, at times, really dirty data (hence the title of this series, “Big Data, Small Data, Clean Data, Messy Data”). And navigating through all those data has always been a team effort.

Yes, there are some exceptional musicians who can write music and lyrics, sing really well, play all instruments, program sequencers, record, mix, produce and sell music—all on their own. But if you insist that only such geniuses can produce music, there won’t be much to listen to in this world. Even Stevie Wonder, who can write and sing, and play keyboards, drums and harmonicas, had close to 100 names on the album credits in his heyday. Yes, the digital revolution changed the music scene as much as the data industry in terms of team sizes, but both aren’t and shouldn’t be one-man shows.

So, if being a “Data Scientist” means being a super businessman/analyst/statistician who can program, build models, write, present and sell, we should all just give up searching for one in the near future within your budget. Literally, we may be able to find a few qualified candidates in the job market on a national level. Too bad that every industry report says we need tens of thousands of them, right now.

Conversely, if it is just a bloated new title for good old data analysts with some knowledge in statistical applications and the ability to understand business needs—yeah, sure. Why not? I know plenty of those people, and we can groom more of them. And I don’t even mind giving them new long-winded titles that are suitable for the modern business world and peer groups.

I have been in the data business for a long time. And even before the datasets became really large, I have always maintained the following division of labor when dealing with complex data projects involving advanced analytics:

  • Business Analysts
  • Programmers/Developers
  • Statistical Analysts

The reason is very simple: It is extremely difficult to be a master-level expert in just one of these areas. Out of hundreds of statisticians who I’ve worked with, I can count only a handful of people who even “tried” to venture into the business side. Of those, even fewer successfully transformed themselves into businesspeople, and they are now business owners of consulting practices or in positions with “Chief” in their titles (Chief Data Officer or Chief Analytics Officer being the title du jour).

On the other side of the spectrum, less than a 10th of decent statisticians are also good at coding to manipulate complex data. But even they are mostly not good enough to be completely independent from professional programmers or developers. The reality is, most statisticians are not very good at setting up workable samples out of really messy data. Simply put, handling data and developing analytical frameworks or models call for different mindsets on a professional level.

The Business Analysts, I think, are the closest to the modern-day Data Scientists; albeit that the ones in the past were less so technicians, due to available toolsets back then. Nevertheless, granted that it is much easier to teach business aspects to statisticians or developers than to convert businesspeople or marketers into coders (no offense, but true), many of these “in-between” people—between the marketing world and technology world, for example—are rooted in the technology world (myself included) or at least have a deep understanding of it.

At times labeled as Research Analysts, they are the folks who would:

  • Understand the business requirements and issues at hand
  • Prescribe suitable solutions
  • Develop tangible analytical projects
  • Perform data audits
  • Procure data from various sources
  • Translate business requirements into technical specifications
  • Oversee the progress as project managers
  • Create reports and visual presentations
  • Interpret the results and create “stories”
  • And present the findings and recommended next steps to decision-makers

Sounds complex? You bet it is. And I didn’t even list all the job functions here. And to do this job effectively, these Business/Research Analysts (or Data Scientists) must understand the technical limitations of all related areas, including database, statistics, and general analytics, as well as industry verticals, uniqueness of business models and campaign/transaction channels. But they do not have to be full-blown statisticians or coders; they just have to know what they want and how to ask for it clearly. If they know how to code as well, great. All the more power to them. But that would be like a cherry on top, as the business mindset should be in front of everything.

So, now that the data are bigger and more complex than ever in human history, are we about to combine all aspects of data and analytics business and find people who are good at absolutely everything? Yes, various toolsets made some aspects of analysts’ lives easier and simpler, but not enough to get rid of the partitions between positions completely. Some third basemen may be able to pitch, too. But they wouldn’t go on the mound as starting pitchers—not on a professional level. And yes, analysts who advance up through the corporate and socioeconomic ladder are the ones who successfully crossed the boundaries. But we shouldn’t wait for the ones who are masters of everything. Like I said, even Stevie Wonder needs great sound engineers.

Then, what would be a good path to find Data Scientists in the existing pool of talent? I have been using the following four evaluation criteria to identify individuals with upward mobility in the technology world for a long time. Like I said, it is a lot simpler and easier to teach business aspects to people with technical backgrounds than the other way around.

So let’s start with the techies. These are the qualities we need to look for:

1. Skills: When it comes to the technical aspect of it, the skillset is the most important criterion. Generally a person has it, or doesn’t have it. If we are talking about a developer, how good is he? Can he develop a database without wasting time? A good coder is not just a little faster than mediocre ones; he can be 10 to 20 times faster. I am talking about the ones who don’t have to look through some manual or the Internet every five minutes, but the ones who just know all the shortcuts and options. The same goes for statistical analysts. How well is she versed in all the statistical techniques? Or is she a one-trick pony? How is her track record? Are her models performing in the market for a prolonged time? The thing about statistical work is that time is the ultimate test; we eventually get to find out how well the prediction holds up in the real world.

2. Attitude: This is a very important aspect, as many techies are locked up in their own little world. Many are socially awkward, like characters in Dilbert or “Big Bang Theory,” and most much prefer to deal with the machines (where things are clean-cut binary) than people (well, humans can be really annoying). Some do not work well with others and do not know how to compromise at all, as they do not know how to look at the world from a different perspective. And there are a lot of lazy ones. Yes, lazy programmers are the ones who are more motivated to automate processes (primarily to support their laissez faire lifestyle), but the ones who blow the deadlines all the time are just too much trouble for the team. In short, a genius with a really bad attitude won’t be able to move to the business or the management side, regardless of the IQ score.

3. Communication: Many technical folks are not good at written or verbal communications. I am not talking about just the ones who are foreign-born (like me), even though most technically oriented departments are full of them. The issue is many technical people (yes, even the ones who were born and raised in the U.S., speaking English) do not communicate with the rest of the world very well. Many can’t explain anything without using technical jargon, nor can they summarize messages to decision-makers. Businesspeople don’t need to hear the life story about how complex the project was or how messy the data sets were. Conversely, many techies do not understand marketers or businesspeople who speak plain English. Some fail to grasp the concept that human beings are not robots, and most mortals often fail to communicate every sentence as a logical expression. When a marketer says “Omit customers in New York and New Jersey from the next campaign,” the coder on the receiving end shouldn’t take that as a proper Boolean logic. Yes, obviously a state cannot be New York “and” New Jersey at the same time. But most humans don’t (or can’t) distinguish such differences. Seriously, I’ve seen some developers who refuse to work with people whose command of logical expressions aren’t at the level of Mr. Spock. That’s the primary reason we need business analysts or project managers who work as translators between these two worlds. And obviously, the translators should be able to speak both languages fluently.

4. Business Understanding: Granted, the candidates in question are qualified in terms of criteria one through three. Their eagerness to understand the ultimate business goals behind analytical projects would truly set them apart from the rest on the path to become a data scientist. As I mentioned previously, many technically oriented people do not really care much about the business side of the deal, or even have slight curiosity about it. What is the business model of the company for which they are working? How do they make money? What are the major business concerns? What are the long- and short-term business goals of their clients? Why do they lose sleep at night? Before complaining about incomplete data, why are the databases so messy? How are the data being collected? What does all this data mean for their bottom line? Can you bring up the “So what?” question after a great scientific finding? And ultimately, how will we make our clients look good in front of “their” bosses? When we deal with technical issues, we often find ourselves at a crossroad. Picking the right path (or a path with the least amount of downsides) is not just an IT decision, but more of a business decision. The person who has a more holistic view of the world, without a doubt, would make a better decision—even for a minor difference in a small feature, in terms of programming. Unfortunately, it is very difficult to find such IT people who have a balanced view.

And that is the punchline. We want data scientists who have the right balance of business and technical acumen—not just jacks of all trades who can do all the IT and analytical work all by themselves. Just like business strategy isn’t solely set by a data strategist, data projects aren’t done by one super techie. What we need are business analysts or data scientists who truly “get” the business goals and who will be able to translate them into functional technical specifications, with an understanding of all the limitations of each technology piece that is to be employed—which is quite different from being able to do it all.

If the career path for a data scientist ultimately leads to Chief Data Officer or Chief Analytics Officer, it is important for the candidates to understand that such “chief” titles are all about the business, not the IT. As soon as a CDO, CAO or CTO start representing technology before business, that organization is doomed. They should be executives who understand the technology and employ it to increase profit and efficiency for the whole company. Movie directors don’t necessarily write scripts, hold the cameras, develop special effects or act out scenes. But they understand all aspects of the movie-making process and put all the resources together to create films that they envision. As soon as a director falls too deep into just one aspect, such as special effects, the resultant movie quickly becomes an unwatchable bore. Data business is the same way.

So what is my advice for young and upcoming data scientists? Master the basics and be a specialist first. Pick a field that fits your aptitude, whether it be programming, software development, mathematics or statistics, and try to be really good at it. But remain curious about other related IT fields.

Then travel the world. Watch lots of movies. Read a variety of books. Not just technical books, but books about psychology, sociology, philosophy, science, economics and marketing, as well. This data business is inevitably related to activities that generate revenue for some organization. Try to understand the business ecosystem, not just technical systems. As marketing will always be a big part of the Big Data phenomenon, be an educated consumer first. Then look at advertisements and marketing campaigns from the promotor’s point of view, not just from an annoyed consumer’s view. Be an informed buyer through all available channels, online or offline. Then imagine how the world will be different in the future, and how a simple concept of a monetary transaction will transform along with other technical advances, which will certainly not stop at ApplePay. All of those changes will turn into business opportunities for people who understand data. If you see some real opportunities, try to imagine how you would create a startup company around them. You will quickly realize answering technical challenges is not even the half of building a viable business model.

If you are already one of those data scientists, live up to that title and be solution-oriented, not technology-oriented. Don’t be a slave to technologies, or be whom we sometimes address as a “data plumber” (who just moves data from one place to another). Be a master who wields data and technology to provide useful answers. And most importantly, don’t be evil (like Google says), and never do things just because you can. Always think about the social consequences, as actions based on data and technology affect real people, often negatively (more on this subject in future article). If you want to ride this Big Data wave for the foreseeable future, try not to annoy people who may not understand all the ins and outs of the data business. Don’t be the guy who spoils it for everyone else in the industry.

A while back, I started to see the unemployment rate as a rate of people who are being left behind during the progress (if we consider technical innovations as progress). Every evolutionary stage since the Industrial Revolution created gaps between supply and demand of new skillsets required for the new world. And this wave is not going to be an exception. It is unfortunate that, in this age of a high unemployment rate, we have such hard times finding good candidates for high tech positions. On one side, there are too many people who were educated under the old paradigm. And on the other side, there are too few people who can wield new technologies and apply them to satisfy business needs. If this new title “Data Scientist” means the latter, then yes. We need more of them, for sure. But we all need to be more realistic about how to groom them, as it would take a village to do so. And if we can’t even agree on what the job description for a data scientist should be, we will need lots of luck developing armies of them.