In this post, I present a few practical pointers for someone wanting to start a career in the Data Science field.
This week, Silvana (from Switzerland) asked me:
“I’ve been working for seven years in Business Analysis, Data Modelling and Development. I love working with data, and I was considering the idea of getting a full-time role in Data Science; but how can I do this?”.
With no doubt, the Data Science field is getting all the attention these days. From one side, organisations wanting to get the best possible value from their data; and on the other side, different types of professionals looking at Data Science as the opportunity to start or move their career into the amazing world of Data Science. Then, the common question is where to start?
Self-Assessment
Do you have the skills? How easy or difficult is going to be? Let’s begin by understanding who does what in Data Science. There are different roles in the field, and the best start is by mapping your current skills into the skills required for each position.
DataCamp has done an excellent job documenting all roles in Data Science; extensive information can be found on their website. I recommend using their infographic to learn more about the different roles and the skills they require.
Did you find any skills missing after completing the skill assessment? I am pretty sure there will be a skill shortage, but don’t worry this is something that can be fixed.
Get the Skills
The skills used in Data Science can be grouped into two main areas:
- Soft Skills: In summary, you need to know how to work with people. Understand their needs and make their problems yours; this way you will be in a better position to devise a solution. Also, problem-solving skills and understanding of a particular domain knowledge or business process is a plus. Once you master these skills, you will be able to speak to anyone using a language that is familiar to them, and they will feel their requirements are well understood.
- Technical Skills: These are the skills you will use to build the solution. Here I propose a few options to learn the new trade:
- Boot Camps: You have to study! Short-term courses are the best way to invest a few dollars and to start getting a feeling for the new career. Try the formula: Low Investment + Short Duration + High-Value.
- Meet Ups and User Groups: These are groups of data aficionados getting together once a month to discuss techniques and tools and how to use them in the real world.
- Volunteering: Find organisations where you can put your skills to the service of the community on a pro-bono basis. For example, in Sydney, GoodWill Analytics brings data scientists from all different backgrounds together and over a weekend use data and analytics to make valuable contributions to Not-For-Profit Organisations. Being part of this event is a must, it is a unique opportunity to be part of a team of data professionals, and see how data science is used to solve real problems.
Get a Job
Luckily enough, with a few skills under your belt, you should get a job. Personally, I found that roles, where you have to support existing solutions, give you space and time to review what was built, how it was implemented and identify reusable components that can be used to extend the solution in-hand or an entirely new project. Consider a support role as part of your learning path; it will give you the valuable knowledge that will help you advance your career faster.
Also, when looking for a job, you should define your target employer based on the skills you can offer and the value you can generate to improve their business.
“Data Scientists must understand the business processes and bring with them experience in the required field (a market, industry or business process). Usually they are hired as in-house resources. When they start working for a company, they spend time learning about how the business operates, only then they are in a good position to create different analytical data models reflecting the business’ reality.
The Data Architect role, on the other hand, can be filled by either someone internal or external to the organisation. The person in this role uses their experience to prepare, build and manage the systems used by Data Scientists. So, if you are a consultant or sole-trader, Data Architecture is where you will have more chances to get your next job”.
This is just a theory though, but I believe it is applicable here.
Final Thoughts
- In technology, whatever role you have, will require growing your skills and knowledge in a particular field of specialisation consistently.
- Whatever decision you make for your next career move and whatever role you end up having, remember to do it with passion. Don’t look for motivation anywhere except in the passion you have for the work you do. You will find that more than a job, your career can become a way of living while enjoying what you do.
“If we stand still, we’re going backwards. We’ve got to keep moving forward and appear to be moving forward”. (Phil Brown)
Some Data Science Boot Camps you should consider: