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Data Science is a hot topic of the decade, especially in the tech industry. According to the U.S. Bureau of Labor Statistics, data science jobs will rise up to 28% by 2026 - approximately 11.5 million new jobs. The best part is that choosing a career in data science will not only help you earn a good salary but also gives you a high level of job satisfaction. Reports say that it tops the chart in the survey of jobs with the most job satisfaction.
However, enthusiasts are still confused about how to kick start their career in data science. Being one of the hot job profiles, graduates who are looking to start their career and those who are looking to switch career are equally looking forward to a spot in data science. The good news is that Glassdoor has reported over 27,000 job listings in data science in the US alone, and Asia too is catching up!
Read Also: How to become a data scientist in Hong Kong
But the reality is that grabbing a spot in the career may not be an easy task as the roles in data science demand a lot from you in terms of qualifications and attitude.
Here let us have a look at some of the optimal ways to activate your data science career.
Just like everything you do, getting the basics right is what matters the most. So invest enough time on the learning part and get to know in detail about what you are up to. The best part is giving you some considerable time to learn the tricks and tips of data science trading rather than rushing into it.
Invest at least 1 year to learn the basics of programming languages like Python and do more reading to get better insights into big data analysis. And it is always better to mix up your learning avenues including textbooks, journals, and online courses, or even by listening to podcasts. Much of this learning process can be accelerated with data science immersive bootcamp, where you'll cover a lot of ground in half the time.
Let's be clear on the type of roles that are awaiting you in a data science career. Aspirants usually target the most promising spot of data scientists alone while leaving behind other significant roles in data science.
Of course, data scientist is a dream roledata-science for many with great exposure and awesome salary packages. But if you are a software developer looking to switch to a different role, a data engineer can be a good option.
Similarly, you can opt for other demanding options in data science including Business Intelligence (BI) developer, Data Architect, Applications Architect, Infrastructure Architect, Enterprise Architect, Data Analyst, Machine Learning Scientist, Statistician and a lot more.
Every role is different and may not suit you but may suit someone else, so do a lot of thinking about which role our would be great for you. Be very clear about which role you are looking for and work towards it. Make sure you consider the difficulty level of learning data science since it is technical.
Once you have decided the type of role, the next step is to join a relevant course that specializes in that particular domain. Xccelerate offers full-time full-stack Data Science & Machine Learning Immersive Bootcamp, perfect to start your career in Data Science and Machine Learning industry. A constant and determined effort is needed from your side to learn the A to Z of the role and continue doing it. There are numerous courses and certifications available to help aspirants like you. But your role is to go for the relevant course that can actually help you to achieve your dream.
Read Also: Four Lessons I Learned During A Data Science and Machine Learning Bootcamp
It is very common for people to get caught up in the theory alone. So make sure that you don't make that mistake. Focus more on the practical application which will help you in the long run. Try applying the theory in your daily life scenarios to see how analysing data works.
It is beneficial to be familiar with Excel tools as Excel enables you to see how manipulating data gives you results.
Practicing with case studies is another great option and more importantly, plan for weekly reviews to recognize your weaknesses and work on them. Before moving into the mainstream, you can try building your own small applications to see how it works.
Also, practice explaining complex problems to masses which will be an added bonus once you become a data scientist as you will have to communicate insights to end stakeholders.
Being technically profound doesn't simply make you an automatic entry in data science interviews. What an interviewer looks for most in a candidate is his/her communication skills, which is a critical key to progressing in this career. Being a good communicator is essential to be able to share the analytic ideas with your team and even to convey your points in a meeting.
Having a great idea in your mind and failing to express it through communication is just that… a failure! So try out options to work on your communication skills even before you plan to attend an interview for the role.
In addition to being a good communicator, go forward and participate in full fledge collaboration to unleash your talent. Joining peer-to-peer mentorship programs can be a great idea. Beginners of data science can use this as an opportunity to learn to know the right people. Request them to share their thoughts on your work rather than plainly requesting mentoring.
Invest some time to publish your works online which can be an asset to showcase your skills at the time of interviews.
It is always a great option to make the best use of social media platforms which can have a greater impact than you can imagine. It is good to foster your network with like-minded people. Have a check on the data science events and online groups where you can find a handful of people that can actually be good support and inspiration.
You may start off with very few people you really know well and then expand your network on the go. Stay social and make sure that you don't miss out on any crucial events of top firms when they unleash new technologies. More importantly, keep informed about the top stories in the data science industry which will definitely help you to stay up front in the competition.
Once you are into it, make sure that you polish your digital footprints to grab the attention of people looking for enthusiasts like you. The best part is to curate your LinkedIn profile and prepare an outstanding CV that defines your importance to the organization. Learn to showcase your education and experience and let the firms reach out to you.
It is time now for filtering your positives and leaving behind the negatives. So stay focused on your interests and be passionate about grabbing the spot with excellent determination. Never wait for top companies to start with but consider small companies or start-ups where you will be challenged more.
Analyse the competition and differentiate the skill set from yours to people who are already hired previously. Prepare well for the interview and showcase yourself as an asset to the organization.
Don't forget to bring examples of your past work which they can refer to understand you more. Also, be prepared to ask a few questions on relevant areas in data science rather than simply answering the questions posed to you.
Never think that your job is done once you are selected for your dream role. Consider it as just the beginning and work towards improving your skills every day. It is important to revise the basics whenever needed and build a mindset to always learn, seek feedback and work on your flaws to upskill yourself. Learn to be proactive in the situations and stay flexible enough to be fit to the organizational goals.
Always see the bigger picture and make sure that you are providing value and revenue to the company and consider switching your approach if you are not. Learn to talk to the right people and never hesitate to ask for help when needed. It is good to have a mentor who can bring the best in you.
As we have discussed, the most important step towards activating your data science career is to learn the ins and outs of the role you are up to. Taking up a relevant course that gives you practical insights into the role is the key. If you are already working in a different career or if it is difficult to manage time for yearlong courses, you may consider taking a data science immersive bootcamp.
Read Also: 2021 Career Guide: Data Science & Machine Learning in Hong Kong
Xccelerate offers advanced bootcamps for aspirants who are looking to kick start their career in data science. You can learn everything from the basics to the most advanced skills in our 16-week bootcamp. They even offer scholarships to help underprivileged communities to achieve their career goals.
Moreover, top firms like Microsoft are hiring the best candidates from those who are enrolling for the bootcamp. A realm of possibilities awaits you at Xccelerate including entrepreneurial inspiration and empowerment, enhanced problem-solving skills and more importantly you will learn 'how to learn'.
The demand of data science is on the rise and it is no wonder why employers are investing heavily on choosing the right people for their firm. Being an aspirant, taking the right steps is really important as the competition is too tough to give you a second chance.
