Higher salary. New challenges. Misfit with recent boss. Desire to get hand on much larger sets. Or pure world peace. None of the above is the main reason for data analysts to change their job. But what is then?

Not just American beauty contests, but also job interviews have quotes like “I wish a world-wide peace”. These are ridiculous statements on why you decided to change the job. I interviewed more than 350 people in my career and thus there is no shortage of even bizarre statements like “My father greats you, he thinks Allianz is still very good company and hopes you gonna get me the job.” Since 2017 I have been doing the interviews in a new country. I thought I would be learning some new “world peace” equivalents of this market. However, my surprise has been much bigger.

Loneliness as the denominator

I felt sorry for the guy, when it appeared in first interview. But when second, third and then forth candidate has come up with same reason of leaving recent job, I got on my toes. I thought if this market is some kind of fairy-tale kingdom cursed by mighty wizard. I could not comprehend, why so many people have loneliness as the common denominator of their life. This was not relationship- or friend- kind of loneliness. Rather this was all about work, the analytical loneliness.

How the story goes …

You graduated from some technical or IT-savvy economic university. You love puzzles and quizzes, you loved Math competitions and finding new interesting links between things. Thus, you look around the job market, where would you be able to put your talent into use. You attend several interviews and find out, that your potential employer has serious data conundrums ahead and that analysts would be measured against demanding criteria. You are thrilled. This is exactly what you are longing for: Let some task beat the f**k of you, so you can learn something new.

The first weeks on job is really fun, indeed. You discover new data that nobody analyzed before you. (even after you, but this you will find only later on). Demanding analytical tasks turn out to be a rather trivial data queries, often falling into reporting only category. But work is fun, so never mind. Your boss does not really understand the nitty-gritty of your work, he would not be up to finding you mistake in your queries. But he is really nice. Time flows, you achieved your quarter, year one, two … oh, man, how the time flies.

To your second Christmas in the company you beg Santa for a new boss, new project or at least the new version of the software you are working for. Just to get some progress ahead in your work life. You try to switch the job, try Start-up, Large corporations, family-driven business… Always few moments of thrill and then Yo-Yo effect of frustration hit as with diet. In the turmoil of internal fight, you sign up for expert conference. After all, one can get inspired externally as well. You meet a lot of stand-ins with same spark fading in the eye.

 Loneliness of data analysts

With a bit of the alteration this was the common plot of all 4 candidate stories. None of them asked for salary of company benefits. None of them was investigating the chances of career growth in future. All they were interested to hear was WHAT and UNDER WHO’S LEADERSHIP will I work on? The usual comment went like “In my recent job I am the only one doing data science. Nobody understands that matter, I have no one to consult my approaches. I only know what I googled out on stackoverflow.com or similar portals. I feel lonely!”

It is interesting. When I gave it a deep thought, I realized I can find stories like that in my friend circles, too. The job of analyst is now going through strange wave. There is enormous demand for data-analyzing people. However, since Data Science is very young branch of analytics, there is very few managers, who actually did the Data Science themselves. Analysts often report to managers, you are not experts in the area. Thus, the young data scientists are doomed for the path of the bonsai: Nobody expects you to grow big, they water you time-to-time, but you are just cartoon of the real tree. The limitations of the expert growth of analytics (subject to another blog coming soon) are dire. These candidate stories only remind me of that again.

The same chorus 3 times again

Now it is clear to me that these were not isolated outliers. Sadly, the analysts’ loneliness is indeed a bitter interplay of three factors. Firstly, there is still very few data scientists. Therefore, it is unlikely that more people with this same job description bump into each other in the same company. Controlling, reporting, data engineers, these are all “multiple repeating’s” jobs in the same firm. But sophisticated analytics is often rather lonely. As a result, deserted Data Scientists do not experience team spirit, they have nobody to consult with their assumptions of uncertainty.

Second factor heating the loneliness is absence of managerial leadership. Sophisticated analysts often find themselves within teams that deal with data only marginally (e.g. sales or marketing). Or the teams work with data, but just to report on structured databases. As a result the Data Scientists do not receive proper feedback on their work and are set to learn only from own mistakes (which they have to detect themselves the first place). Some torture themselves with self-study portals and courses, but few have the iron self-discipline to do these for several years in row. Sooner or later, the majority just throws the towel.

The two above mentioned forces are joined by the lack of external know-how as the third factor. No offence here, but if you want to experience conference where each speaker of the day contributed to your growth, you probably have to organize one by yourself. No jokes here, trust me, my own experience speaks here. Expert conferences are rarely organized by people who can tell if the speaker is beneficial or not. Most of the  Data Science events are vendor-brainwashing or people-headhunting traps. That is why (in the popularity ever rising) Meetup’s are often the only remedy for the expert conference hunger.

How to brake the vicious circle?

Even though our dispute might not suggest so, there is a happy-end for the 4 lonely candidate stories.  Although they represent a sad probe into soul of the contemporary data analyst, they also show a way how to brake the vicious circle.  Based on their talks and my own expert experience I would suggest you following 3 steps out of the loneliness:

Step 1: Self-diagnostics. The real change can happen only if participants admit there is an issue to address. This makes the change needed and unavoidable. Thus, please give yourself following 3 questions:  1] Do I have a boss, who understands my job to extent that (s)he would be able to temporarily step in during my absence?  2] Is there somebody else in our company that I can ask if I am doing my Data Science tasks correctly or give me tips if I got stuck?  3] Did I have a chance to get my hands dirty on at least 2 new analytical approaches that I never tried before over the last 6-9 months?  If at least one “NO” emerged  for you in previous three questions, you should seriously think about your analytical future.

Step 2: Deep breath before the dive. If you self-diagnosed yourself for a move ahead, do not run to job portals to look for new job ads. Before you embrace the switch, get ready for the leap. If you start looking for a new job now right away, you will most likely fail to get one. Grab a bit of self-discipline. Take some on-line courses, watch YouTube videos on your new desired expertise. But foremost,  force yourself to really try by your own hands the new skills that you will need in new job.  Maybe start here.

Step 3: Look for real Data Science leader in real Data Science team. To escape the analytical loneliness for real, one has to solve all the three underlying factors. Therefore, .. (a) you have to find a job, where you will be .. (b) part of the larger team working on Data Science and the team … (c) will be led by person with own, real analytical experience.  Team that has ambition to work on plenty of new, analytics relying projects.  Don’t get fooled by sexy offers of companies where one of the 3 aspects is hyped. Start-up’s often look as cool place to work, but often is accompanied with inexperienced founder who “just” had a great idea OR dire DYI conditions that leave you weak to unreliable systems or unskilled neighbor teams. I advise you to start the search by nailing down interesting projects and check on who is leading them.  Alternatively, you can start your search from respected analytics manager and check is his team works on something that would make you dream big again. With high quality managers do not bother to revisit your former bosses’ profiles as well. As they say in airplane security instructions: “Look around, as your nearest emergency exit may be located behind you as well”.

On final note, let me emphasize that analytical loneliness might be a cyclic phenomenon. As the Data Science industry takes traction, teams will grow and finally form generation of nature Data Science leaders. However, in our region it make take well 5-7 years before happening so. Hence, probably a bit too long of a period to “shelter against the storm” in your recent hiding. Thus, if you identified yourself with some aspects of analysts’ loneliness, do not sooth yourself, it will get better sometime. Repeatedly do the same stuff, in stable, well-payed job, where my boss does not know enough to mess into my job or to fire me, can sound like recipe for nice life. So rather than galvanizing you to action, I ask you to give it a thought: How will the whole industry shift in the meantime? How do my chances to switch to more sophisticated analytics improve/worsen as I enjoy the “invincible” times? No matter if you decide to stay or get ready for the leap, let me wish you months (or years) without analytical loneliness.