Starting a Career in Data Science?
In the modern era, starting a career is not that difficult thanks to various colleges, institutions, and universities that have adopted Data Science in their regular curriculum. Moreover, due to the presence of online classes, several students as well as working professionals are getting their certification from reputed professional training institutes and are enjoying a prosperous career in the domain of data science.
A career in data science is highly rewarding as various industries are hiring professionals who are great in data analysis and are proficient in similar stuff. Top HRs and recruiters are on a constant lookout for skilled data science professionals. Did you know – according to Forbes Data Scientist is one of the hottest jobs of the 21st century? If you are planning to start a career in Data Science this is the best time as Naurki.com has 19375 jobs available for candidates in their portal.
You will be glad to know that the U.S. Bureau of Labor Statistics predicts strong growth in the role of the data science field and states that the number of jobs will increase by about 28% through 2026. The scope of data science is huge as every SMB and enterprise wants to know what to do with the data that is available to them; how to process it and convert it into useful information.
15 Tips to Start a Career in Data Science
Do you want to start a data science? Are you willing to take the charge in your hand and take your career to a whole new level? Have you got stuck in your current job position and want to power ahead your career? If yes, then you have come to the right place as we are going to see 15 tips to start a career in data science. Starting a career in data science depends on myriads of facts and we are going to see them all in brief.
There is a slight margin between good and great data scientists and if you are going to follow the below 15 points then no one can stop you from being one of the best data scientists in the world. With the acquired skills you can revolutionize any industry and everyone will welcome you with open arms and hearts.
Here are the 15 tips to start a career in data science:
1. Hone your mathematical skills:
It is a rule of thumb that every data scientist must be good at mathematics so it is quite pivotal that every data scientist must start polishing their mathematical skills.
A data scientist will have to analyze data and convert it into actionable insight; collect vast data and organize them into a structured format. Data science is all about finding patterns and it can be achieved only with the help of a strong foundation in math.
2. Learn Python, R, and SQL:
To become a great data scientist knowledge of certain programming languages as well as databases is compulsory. Learn Python, SQL, and R and prove that you possess all the skills and knowledge required to become an asset to an organization.
With these aforementioned programming languages and a firm knowledge of databases, you can easily start working with a private or public sector organization. These programming languages will make you an outstanding coder and will assist to boost your statistical computational skills.
3. Do internships:
Doing an internship is a great way to acquire relevant data scientist skills. Many candidates think that they will not get paid during the internship but that’s not the point at all; gaining skill is! Go for an internship in an MNC or even a startup organization to know how an organization works within departments and skyrocket your hands-on experience via practical knowledge.
Prepare well by practicing a lot before the interview as this will be the deciding factor for your career. With an internship, you will have the opportunity to solve real-world problems, and also you will get real-time feedback on your performance which is necessary to boost your confidence if you want to become a very good data scientist.
4. Go for professional training:
Enrolling yourself in a reputed professional training institute is highly recommended if you want to attain skills and knowledge that will make you a great data scientist. A professional training institute has mentors and instructors that are willing to make you learn data science with their huge experience.
These professional training institutes teach you the basics and advanced concepts of data science via real-life examples and projects which go beyond the typical classroom approach. Also, you will be given a reputed and valuable certification once you have successfully completed the data science training.
5. Begin as a data analyst:
Numerous candidates think that data scientists and data analysts are the same but that’s a myth. It is advisable that you should start working as a data analyst and once you have gained enough experience and knowledge then you can move towards being a data scientist.
A data analyst’s role is to manage data collection and perform identification of dataset trends; they might not be involved with the coding part. But a data scientist has to be well-versed with coding concepts as well as we have already seen that in point no. 2.
6. Create a strong network:
By creating a strong network we mean to say that you should create a strong connection with people who are already working as a data scientist. Why? It is because doing so will help you gain knowledge in this niche and also they can help you recommend their respective organizations for the job role of a data scientist if they have vacancies.
Through your network, you can seek assistance if you are stuck in any project or simply if you want to clear your doubts. You should join online communities, groups, and forums because their people are always willing to help each other. Try LinkedIn if you want to build your network as you can see hundreds of data science groups in that particular platform.
7. Enhance your communication skills:
A person with good communication skills is always welcome to any organization. As a data scientist, your organization will ask you to understand the business requirements or solve the real-time problem at hand and all these require great communication skills.
You will also have to probe the stakeholders so that you can gather data from them and communicate key data insights so that they can understand your approach. Good communication skills are a must because at times you will be asked to give a presentation on short notice for the solution that you have come up for a defined problem. Without proper communication skills, your journey towards building a data scientist will be difficult.
8. Know business strategy:
A data scientist always needs a strong and determined head for business strategy. They must have a knack for knowing all the ins and outs of a business and the simplest and most effective ways to reach and complete business goals.
It is an admirable quality for data scientists if they have the ability to comprehend business problems and perform analyses from the standpoint of a difficult or complex problem statement. This makes data scientist build their infrastructure to help them understand the data in a way that is useful to the respective organization they are working.
9. Focus on practical applications:
Focusing only on the theory part won’t help you become a great data scientist; you will have to concentrate thoroughly on the practical applications of becoming a data scientist.
Practice coding and database query every day for at least 2-3 hours and you will see that your basics are getting clearer day-by-day and your interest in becoming a data scientist is increasing drastically.
10. Read a lot:
Follow online resources that have lots of articles and blogs related to data science. Read a lot of posts that are being published by the most influential data scientists. These data scientists are quite active and they always update their ardent followers on the findings they have obtained and frequently post about the modern advancement in the field of data science.
Try to read at least 2-3 blogs or articles per day to stay relevant with the modern trends of data science. There are numerous data scientist’s blogs on the internet so don’t get distracted. Always follow the best practices of data science as a few blogs may ask you to do the opposite.
11. Build an outstanding resume:
What’s the first and foremost thing a recruiter will see when you are going for an interview in your dream organization? You have guessed it right – it is your resume! Give lots of time to build an amazing resume that will help you stand amongst the crowd. Write all your skills, hobbies, and relevant knowledge in a way that will impress your would-be boss.
To build a resume that is impressive – follow the below guidelines:
- Mention data science projects in the resume to exhibit your skills
- Never forget to mention your GitHub profile in the updated resume
- Prioritize the skills in your resume as per the job role
- Update your projects and skills side-by-side
- Remember, the overall resume counts so, ensure all your fonts are uniform and formatting is done accordingly
12. Never stop learning:
A time might come when you are going to think that you know a lot about data science but that’s not true at all. Data science is very vast and to delve deeper into this domain you might have to spend 8-10 years in an organization and have to perform the toughest of jobs.
Always remember that experience comes with the passage of time so you have to be patient. Never be over-confident. Stay ahead of the curve by learning every day! Try to know something new in the field of data science that will help you climb the ladder of success quicker than your peers.
13. Emphasize teamwork:
You are only as good as your team so always embrace collaborations and become a good team player. Working together helps to generate better ideas and it also promotes creativity. It also boosts productivity and brings out the best in everyone by yielding the best results.
In data science, teamwork helps you to overcome calculated risks and helps you learn faster from each other. Last, but not least, teamwork enhances employee morale and renders the best motivation. So, when you are being a good team player – you will find that you are becoming a better data scientist every day.
14. Lean-to visualize data:
It is very important to visualize data if you want to become one of the best data scientists in the world. Data visualization always sits right next to each other in the realm of visual storytelling and technical analysis.
As you might know that Big Data is becoming progressively essential to almost every business; data visualization is also becoming a key tool in the process of making sense of the huge volumes of data that are being generated every day. Also, a data scientist should be able to visualize the given data using various tools available in the market such as ggplot, d3.js, and Tableau.
15. Select the perfect role for yourself:
There are myriads of roles available for an aspirant in the industry of data science. A few of them are: a data visualization expert, a machine learning professional, a data scientist, a data engineer, and more. Depending on your background and the interest you possess, getting into one particular role would be a lot easier than any other role.
For example, if you are already a software developer then it would not be that tough for you to shift into a data engineering role. That is why until and unless you are clear about the fact – what you want to become; you might stay confused about the actual path that you are going to take and the required skills to hone in order to become a great data scientist.
Mistakes to Avoid When Starting Your Career in Data Science
If you are new to the field of data science then you are bound to make certain mistakes and for the sake of yourself, you must avoid these. To become a successful data scientist you must only be good at programming skills but you need to master communication, decision-making, and problem-solving skills as well.
If you are good at math then it’s great as you can become a skilled data scientist but if you are not too well with mathematics then your way to becoming a data scientist will be paved with lots of difficulties.
So, here are the top 5 mistakes to avoid while starting your career in data science:
- Learning theoretical concepts and not apply them: To become a successful data scientist always apply the theories in real life that you have learned. If you fail to do so then your knowledge will stay limited.
- Always focusing on the tools: Instead of only focusing on the tools you should concentrate more on learning new things in the niche of data science. When you focus on the tools as well as learning equally you will see that you are evolving day-by-day in becoming an amazing data scientist.
- Performing data analysis without any plan: Ease of availability of data often makes a data scientist jump directly towards the data without having any well-defined question. This might be dangerous for any data science project because data science is a structured process that starts with well-defined questions and objectives. Always ask a question; always!
- Using too much jargon in the resume: Never ever try to show-off in your resume by having too much jargon. Your resume must have bullet points and it should tell a story on how your skills and knowledge will prove crucial to an organization on the occasion if you got selected.
- Not having a structured approach towards problem-solving: Remember, not having a structured approach towards problem-solving is counter-intuitive and it is never welcomed in an organization; Your approach and work towards a problem will be hit-or-miss, and in the end, you might lose track of your own steps and progress when you are solving a complex problem.
So, now you know how to start a career in data science. Don’t rush and take every step carefully on the way to become a successful data scientist. Enhance all the relevant skills in the domain of data science. Don’t be shy to take help or assistance from others because, in the end, it is you who is going to get benefitted. Build a strong network of people who are experienced in data science and take guidance from them if you are working on a project. Read a lot of data science blogs or articles and don’t forget to build a resume that will help you make all your dreams come alive.
Why Learn Data Science from Ethan’s Tech?
Study Data Science at Ethan’s Tech and get ready for an excellent future that awaits your presence. Join our Data science training classes in Pune or Noida and become a successful data scientist professional. Attain relevant knowledge and skills from mentors and instructors who are leading names in data science. Learn basics and advanced concepts of Data Science such as Exploratory Data Analytics, Data Pre-processing Data handling Techniques, Algebra, Statistics, Machine Learning algorithms, and Mathematics to get placed in the top organizations of the world. Happy learning!