9 tips to help you get a data science job

Today every organization is thriving on data. It is the fuel that helps enhance the organization’s productivity while helping them focus on the customer’s preferences and choices. All this eventually helps in boosting their competitive levels, thereby putting them up on a global pedestal. Data science plays a significant role in this. Organizations harbor information. Data scientists work on data sets using different tools. Thus, there is a surge in data science jobs across the industry spectrum.

Data science is also one of the well-paying jobs. With the increasing amount of data being generated today, organizations are in dire need of individuals who can easily analyze and interpret data, thus helping them make informed decisions. From food to finance, health care to technology, data scientists are omnipresent. So, if you are wondering how to get a data science job, you will get the answers here.

Key statistics on the growth of data science professionals

  • The demand for data scientists had risen by 28% in 2020
  • Around 83% of the companies are actively investing in Big Data projects
  • Data science started witnessing major growth in 2019.
  • As per the Bureau of Labor Statistics, the demand for professionals with data science skill sets will witness a growth rate of 28% by 2026.
  • Despite the growth, there is still a shortage of skilled data science professionals
data science global demand

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All these stats clearly highlights that the demand for data science professionals is sprouting. And hence, pursuing a career in this domain will give a positive professional growth. Choosing the right career path becomes a perplexing task for freshers and college graduates. Many freshers are now eyeing this data science league. But a common question that pops up is how to get a data science job as a fresher. In this blog, we are going to unfold some of the key details regarding the same.

Want to know how to get a job in data science with no experience: here are some key tips:

  • Focus on the skills and knowledge that you do have

One of the key concerns that freshers have is how to start learning data science when the concept of data science is new to them. While you may not have professional experience as a data scientist, you likely have some relevant skills and knowledge that you can focus on. You can start exploring online platforms and portals where you can get relevant information about data science and the key developments taking place in this domain.  You can include coursework in statistics, machine learning, and programming, as well as personal projects that demonstrate your ability to apply these concepts.

  • Emphasize your passion for data science

Employers are often looking for candidates who are genuinely interested and excited about data science. Make sure to highlight your passion for the field in your resume and cover letter, and be prepared to discuss your interests in data science during job interviews.

  • Consider applying for internships or entry-level positions

Well, starting small can be of great help to you. For example, instead of eyeing a high profile, you can begin as an intern or apply for entry-level positions. It is a great way to gain hands-on experience and build up your resume. These types of positions may also lead to full-time job offers.

  • Network and seek out mentorship

Networking with other professionals in the field can help you learn about job openings and get advice and mentorship. Consider joining relevant online groups and forums, attending meetups and conferences, and connecting with data scientists on LinkedIn.

  • Be open to learning and continuous improvement

Data science is a rapidly evolving field, so it’s important to be open to learning new skills and technologies. Consider taking online courses or earning additional certifications to stay up-to-date and enhance your skills. Here are some tips on how to get your first data science job:

  • Get familiar with the tools of the trade

It’s important to have a good understanding of the tools and technologies that are commonly used in data science, such as programming languages like Python and R, as well as tools like Jupyter notebooks, Git, and SQL. You can gain familiarity with these tools through online courses and tutorials or by working on personal projects.

  • Build up your portfolio

Pursuing a data science certification course is one of the easiest ways to enter this domain. While doing so, you should also focus on building your portfolio by working on live projects and creating yours. Potential employers will want to see what you’ve done, so it’s important to have a portfolio of projects that demonstrate your skills. You can create a GitHub repository to host your code and projects and include a link to it in your resume.

  • Learn how to communicate your work

Being able to communicate your data analysis and findings clearly and effectively is critical in data science. This includes being able to explain technical concepts to non-technical audiences, as well as creating visualizations to communicate your results.

  • Be open to learning and continuous improvement

Data science is a rapidly evolving field, and it’s important to be open to learning new skills and technologies. Consider taking online courses or earning additional certifications to stay up-to-date and enhance your skills.

Finding the right course that offers a data science course placement guarantee:

If you are planning to pursue a career in data science, then rolling for the right data science course is paramount. There are several data science course placement programs, but not every course provider will live up to the claims. Hence figuring out the right institute becomes paramount. Here are certain pointers that should be on your checklist:

  • Look for the course curriculum

The first parameter that should be on your checklist is the course curriculum. Instead of just rushing to the data science course and rolling yourself, you must do thorough research about the course curriculum and the module included in it. Of course, offering you a blended and immersive learning experience will be a good start rather than the one that focuses solely on concept development.

  • The instructors

The team of tutors and instructors on the board of the course provider also plays a major role in ensuring an effective learning experience. Hence, you must also see the different instructors who are present with the course provider.

  • Check the track record

There are several job guarantee data science course providers but not every institute fulfills the claims. Hence before enrolling, you must check the track record of the institute. The number of Bootcamp, Hackathon, and placements offered by the course provider gives you an assurance of whether you should pursue the course or not.

Proceeding ahead

Pickl.AI offers you a complete learning experience wherein you can join their Job Guarantee Program. This data science course not only acquaints you with the concepts of data science but also ensures that you land a well-paying job. Pickl.AI also offers an internship program that gives the right start to your professional journey. So, if you are looking for a data science course for college students with a placement guarantee, join the Job Guarantee Program with Pickl.AI.


Neha Singh

I’m a full-time freelance writer and editor who enjoys wordsmithing. The 8 years long journey as a content writer and editor has made me relaize the significance and power of choosing the right words. Prior to my writing journey, I was a trainer and human resource manager. WIth more than a decade long professional journey, I find myself more powerful as a wordsmith. As an avid writer, everything around me inspires me and pushes me to string words and ideas to create unique content; and when I’m not writing and editing, I enjoy experimenting with my culinary skills, reading, gardening, and spending time with my adorable little mutt Neel.