Skills of Data Scientists

I'm going to be honest with you.  This is a 2-part post about what skills Data Scientists and Digital Analysts need.  Now, I've never worked as either so none of the line items here are informed by my own experience, so you be the judge.  What I can say is that from all of the people I've talked to, and articles I've read, digital analysis, or data science if you are on the more technical side, are rapidly evolving fields.  If you are the type of person who wants to cram for 2-7 years and remain thereafter an expert in your field without constant continued personal learning, swipe right, these roles aren't for you.  I, on the other hand, spent seven years dedicating far, far too much time to coming up with language and pitches that were all essentially the same, selling beauty, luxury, and a vacuous fascination with sparkly items designed to make people feel special.  I am beyond tired of the monotonous view on that treadmill.   So, bring on the learning!  And the challenges, because any headache earned through growth is far more palatable to me than one earned through stagnation.

SKILLS FOR DATA SCIENTISTS

1. Masters degree- Computer Science, MBA. Many have evolved into this role, according to a graph sourced from a Stack Overflow Developer survey.

2. Intellectual Curiosity -  The desire to ask questions, probe for answers, and approach problems in new ways, not to mention explore the the plethora of new resources that are regularly introduced to further analysis in the field.

3.  Business Acumen-  To be a good fit in this role, you cannot hope to operate in a silo.  You need to want to understand the ins and outs of how the whole business works, what's affecting the company and the industry,  and also the cutting edge tools of your trade, all of which which require a fair amount of technical know-how.  This isn't a role that you can get by on with a baseline executive mindset.  

4.  Career Mapping- Even in what feels like a specialized field, there can be more specialization.  So if you see yourself as an interpreter who understands and translates to clients how the technology works, refine your skills to fit that.  If you are pure tech, stay on top of those skills.  I'm sure you get the idea.  Again, consider this is as a guide to operating in these roles successfully, not just jumping in the shallow end.

5. Coding Skills - Bottom line, you need to dig coding, and learning new coding languages, and be willing to learn and understand the scope of the various tools and what they can do.  If the thought of this makes you gag, swipe right.

6. Machine Learning/Data Mining Skills - Just say, for instance, you want to be able to understand how it works without having to be able to do it, because you have some lackeys in the back who don't like the spotlight.  Sigh. This is not the job for you.  Please take your seat at the side of the table and leave the presentation to the experts because your ignorance will soon catch up with you.

7. Big Data Processing Platforms - Data processing platforms are part of of the data science landscape. Know them.  Learn them.  Be ready to learn the next one coming around the corner.

8.  Structured Data SQL - Learn Sequel. It works on relational data. You'll likely need to learn how to work with unstructured data as well.

9.   Unstructured Data NoSQL - Yes this too.  I believe this refers to sound, video, and unlabeled data, which is evolving as we live more of our lives online. You will be asked to work with it to mine for insights.


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