Data science as a career

I'm so new to all this I find it a bit daunting to even know where to begin. How do self-taught people learn this stuff generally?
How comfortable are you with taking your projects and creating a high level diagram of the different classes and related attributes, functions, and interactions between them?

Second, if you are looking to start into databases with SQL your program will need to have a more solid concept of "permanance". You can start with a "dummy" database hardcoded but eventually you will need to be able to dynamically create your database from user/device inputs. These should be able to persist beyond compilation of your program in the IDE. This was a bit of a new concept from the coding background I had when I was introduced to SQL.

Finally, you will soon find set lessons and examples give diminishing returns as you become comfortable with software design concepts and program syntax. Start looking for basic projects you can implement that interest you. Find something functional and add a "data mining" element to it. One of my first projects was literally monitoring moisture sensors on my houseplants and sunlight intensity from a photoeye. The project grew out of a need to use the photoeye to trigger a once a day moisture routine. I shoehorned a database in with moisture readings and light intensity stored as well as the if/then type program triggering watering cycles.
There are paths into data science without needing a degree in it!

An old friend is studying economics and history, and started leveraging R and Python to handle large sets of historical economics data. Long story short over the course of two years it's led to two data science internships, as well as interest from other companies to hire him for data science stuff once he graduates.

According to him, anyone can learn Python, but knowing what questions to ask, as well as having an understanding of calculus and statistics is what's given him success.

I'd say go for it!


It's something I am considering seriously and I wondered if anyone here knows much about it, it's pros and cons.

I am mid 30s and work in finance. Just finishing a professional finance qualification. I gather I would need to learn Python and SQL as well as get very good at statistics. What else is there to be aware of, in terms of the job market, job opportunities, what the work is like and so on?

If you want some job security,
Stay away from trendy fields. Right now, blockchain and AI are the trendy fields. Data science was a trendy field 3 or 4 years ago.
In times of plenty, you can indulge in trendy fields. But right now, I'm pretty sure data science is on the chopping block. There are only some companies that have the scale to take advantage of their data, but there has been a massive amount of hiring in data science over the past few years. This means a lot of companies will soon enough come to Jesus on how useless data science is (most of the products that data scientists produce are not all that special - a regular engineer combined with a good product manager can do it). Plus, there has been a massive number of data science degree grads in recent years, which increases the number of people with these skills on the market.

Data scientists never really make the cut to be software engineers so it's not an entry point.
I know this from personal experience, and Kel is right on all his thoughts.

I've been an advocate of coding bootcamps in the past, but there is a market oversaturation at this point, so I'd say no to bootcamps in general.

Now finance people with SQL skills, that's a good combo. I'd learn as much SQL as you can.
Being a business analyst requires those skills. You can teach yourself SQL, don't pay for training.
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I remember there was a guy who had a website (or maybe a blog?) with an interesting concept he called "programming kata" (as in karate). He came up with coding projects that would increase gradually in terms of complexity. They were also pretty useful things to have completed, not just dummy "Hello world" types. It's a good mix of practising your skills and actually doing something productive. Not sure if it's still there but might be worth a google.


Data science is arguably an ill-defined career path for two reasons: 1) it's still new so there isn't a ton of foundational understanding yet of what it is by companies that look to hire data scientists; 2) even people in the field will give you different definitions of what data science is and there are plenty of poseurs who fluff their resumes with the title but probably stretch the truth about what they do. I've considered the field myself because I have been a data analyst for more than 10 years and when data science first started to pop off, I got curious and started researching what it was all about. That being said, let me offer my perspective on this subject.

First, I know several data scientists and they all say that knowing at least one programming language with a good degree of confidence is essential. Some of the most recognizable names would be Python, R, and SQL. In my opinion, most data science jobs will require a high degree of competency with one of those 3.

Second, extensive knowledge of applied statistics is foundational to being a data scientist. My guess is that if you took college statistics and did well and actually enjoyed its application, you might fare well. Most people need to develop these skills more than what they learned in college and data science will surely require a strong aptitude.

Third, data science seems to be more about doing deep research of a problem, then diving into related available data that helps to see what the problem is really all about, and then the application of statistics to determine the significance of the problem and the right understanding of the path forward. That said, people with a strong background in research are probably well-suited for data science.

Lastly, if you are seriously considering this field, I recommend that you create a presence on LinkedIn and connect with people who have a data science background and establish connections with them and see if someone might be willing to mentor you or help you understand more about the field. There are people on LinkedIn who are very established in data science and have built strong data science communities. Here are some names that I follow:
  1. Eric Weber:
  2. Matt Dancho:
  3. Beau Walker:
Matt Dancho created his own course called Business Science, which teaches you how to apply data science in a business setting. Beau Walker is a very active member of the data science community that I believe also teaches data science concepts.

Check these guys out.

Mr Gee

The corporate world is going through major changes soon I am sure. Once the funny money slows down services like data science will need to show real value to continue as a viable addition to a companies strategy. Data science may consolidate to a cloud like service much like infrastructure is doing now, with regional centres.
I just finished up with a global company, now decimated by the covid lock-down madness. We worked with analytics companies in the US, it was my job to facilitate access to crunch the data on our servers with our own resources. I don't think any useful information came about from the results (if any) over a certain period of time. They were after customer behaviour to predict future revenue opportunities, improvements, or cost efficiency, or something like that it was all rather vague but the boss and finance manager had a handle on all of it apparently. All that was canned in June this year.
Find an industry that still requires this type of work in the foreseeable future and stick with them.
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