15 Tips to Find a Career as a Data Scientist
The rise of big data, as explained over at runrex.com, has necessitated the need for more analytical and highly skilled people to interpret and mine this data for businesses, which is why data science is one of the best careers currently out there in the job market. If you are looking to get started in a career in data science, here are 15 important tips to follow.
- Choose the correct role
Data science, as covered in detail over at guttulus.com, is a wide industry with lots of roles for data scientists such as data visualization experts, machine learning experts, data engineers, and many others. You should, therefore, consider choosing the right role depending on your background and work experience when looking to start a career as a data scientist. For example, it will be difficult to shift towards data engineering if you are a software developer, among other examples.
- How do you choose the right role?
On a related note, given how important it is that you choose the right role when getting started in a career as a data scientist, you may be wondering how you go about choosing the right role. Well, one of the things you should do is figure out what you are good at and what you want, and then choose a role that suits your field of study best. You should also consider speaking to people in the data science industry and figure out what each role entails to help you make the decision.
- Take up a relevant course
Once you have decided on a role, the gurus over at runrex.com recommend that you now try ad understand the role, which you can achieve by taking up a relevant course. You can choose between free and paid courses, with the major factor when choosing a course being whether or not the course helps you not only understand the basics but brings you to a suitable level of understanding that will allow you to push on further.
- Be diligent with your course work
When you choose a course, you have to go all out and ensure that you follow through on it and are diligent with your studies. This means following all the coursework, assignments, as well as all the discussions around the course. Make sure you do the course end-to-end if you want to get a better understanding of the field you have chosen.
- Choose the right tool/language
One question aspiring data scientists have to answer is which tool or language to choose. According to the subject matter experts over at guttulus.com, you should choose the simplest language or the one which you are familiar with, to begin with, and then expand your repertoire once you have grasped the basic concepts. A good starting point is to begin by learning about Python for data science.
- Join a peer group
Joining a peer group is important when looking to get started as a data scientist as they will help keep you motivated given how daunting taking up a new field, particularly one as complex as data science, can be. If you don’t have a group of people you can physically interact with to encourage you, you can check out online forums such as Reddit, Analytics Vidhya, and so forth for the same.
- Focus on the practical application
As is revealed in discussions on the same over at runrex.com, it is important that you focus on the practical applications of the things you are learning and not on the theory when undergoing data science courses and training. By doing so, you will not only be able to understand the concepts you are studying, but you will also be able to gain a deeper understanding of how the concepts will be applied in reality, which will help your career prospects.
- Leverage available resources
It is important that you read about data science every day and update yourself with all the latest developments in the industry as a beginner. To do so, you should leverage available resources like blogs and articles by influential data scientists, podcasts, and so forth. However, given the sheer number of such resources out there, you must follow the right resources so that you don’t end up learning the wrong practices.
- Improve your communication skills
As the gurus over at guttulus.com are quick to point out, communication skills are crucial in data science and could lead to you being accepted or rejected for roles. Don’t just focus on your technical proficiency, also ensure that you work on your communication skills, which will be needed when you get employed as you will need to share your ideas and findings with colleagues or decision-makers who may not have the same background in data science as you.
- Don’t forget to network
If you want to find a career as a data scientist, your initial focus should be on learning and acquiring the technical and soft skills required. Once you start getting a hang of things though, you should also start networking, which includes attending industry events and conferences, participating in hackathons, checking out poplar meetups, and so forth. This will provide you with learning and networking opportunities, allowing you to establish relationships that will help you advance your career as a data scientist.
- Learn from failures
As is revealed in discussions on the same over at runrex.com, starting a career in data science takes time and effort, which means that interviews won’t always go for you, and you may have to deal with one or two rejections, initially at least. An important tip here is to learn from the failures and the interviews that didn’t go as planned, practicing and trying to improve your interviewing skills, and eventually, you will land a job as a data scientist, kickstarting your career.
- Build a portfolio
Employers don’t just want to hear what you are capable of doing, they want to see proof. If you want to find a career as a data scientist, you should not only say what you can do but should also show it, which you can achieve by building a portfolio of your past work and projects. You should save your best work and the best solutions to problems and use them to build an impressive portfolio.
- Find a mentor
Another important tip to follow when looking to find a career as a data scientist is to find a mentor. As is explained over at guttulus.com, a mentor will guide you through projects and educational resources, while also helping you figure out what exactly employers look for in a candidate for a data science position or role.
- Don’t be too choosy
While you may have a preferred position or company you want to work in as a data scientist, you should not be too choosy when you are getting started. Accept the offer that is in front of you even if it wasn’t what you are aiming for. If you work hard enough, you will be able to work yourself towards your dream job as a data scientist.
- Don’t ignore internships
You should also not make the mistake of looking down on internships, even though you want to get a full-time paid gig. Internships are great at building job experience, and may even lead directly to a full-time position in the company or organization you are interning at.
Remember, if you are looking for more information on the field of data science, then look no further than the highly regarded runrex.com and guttulus.com.