A career in data science is enriching and resilient to significant global changes. In fact, the demand for data scientists increased exponentially during Covid-19 and the recent global economic recession. When unemployment rates were at their highest during the pandemic, data science professionals took home a base annual salary of almost $200,000 as individual contributors and a yearly salary of up to $300,000 as managers. Unlike other conventional jobs, a career in data science demands the right skills, advanced knowledge, and experience.

This article has put together the critical steps to finding data science jobs and making the next big move in your career. 

1. Working on advancing your data science skills

In fact, data science jobs are among the 50 Best Jobs in America for 2022. Yet, employers have difficulty scouting the right talent for these jobs. Before starting your job hunt, you must have the right technical, analytical, and soft skills. 

  • Master programming languages like Python, R, or SQL.
  • Get familiar with important mathematical and statistical concepts.
  • Develop a fundamental understanding of machine learning.
  • Learn a few data visualization tools such as Tableau.
  • Polish your communication skills.

If you are interested in developing essential data science skills, you can learn these skills or upskill them with the help of Seekho

2. Getting relevant experience 

Although 11.5 million data science jobs will be created globally by 2026, landing an entry-level job is no less than an achievement. Furthermore, due to the complex nature of data science jobs, organizations look forward to hiring experienced data scientists. Therefore, in an industry where real-world data experience is essential, it is essential to have relevant hands-on data science experience. 

  • Coding challenges and hackathons are among the best platforms to utilize and advance your data science knowledge to build practical applications. They also help you connect with leading data science professionals of the industry and sometimes even possible recruiters.  
  • Open source projects help you gain valuable experience as millions use your work daily. You can choose projects as per your convenience and interest. Open-source projects are extremely helpful in developing analytical skills, learning from feedback, and gaining experience that recruiters value.
  • Personal data science projects will help you learn vital data science skills if nothing else works. You can also showcase your knowledge and understanding of the nuances of data science through these projects to recruiters on GitHub.

3. Building a portfolio to showcase your data science skills

It is important to build a portfolio to showcase your data science skills. A portfolio is documented evidence of your data science skills and passion for it. An impactful portfolio is sometimes enough to land you a lucrative data science job.

4. Creating a powerful resume that stands out

Once you are thorough with developing and advancing your data science skills, it is important to build a resume that takes you closer to your desired data science jobs. A well-drafted resume is crucial in your job search as most organizations these days utilize software to shortlist applications. You can either use online resume templates or deploy professional help to create an impressive resume.

5. Describing your work

The technical team comes into the recruitment process much later. The human resource team does the initial screening and may not have the data science technological know-how. It is always advisable to add descriptions to your projects on Linkedin or other job portals. These descriptions help HR managers from non-technical backgrounds to understand your skills. You could also write blogs to showcase your work and skills. However, suppose writing blogs do not come naturally to you. In that case, you can write the details and background of your project in non-technological terms in the readme document in the Git project folder or Kaggle notebooks.

6. Networking with data science professionals

Data science job roles are one of the highest-paying jobs. The national average salary for a Data Science is $95,359 in the United States. In India, the national average salary for a Data Science professional is ₹11,11,500. Since employers look for high competency in prospective employees, most data science jobs are recruited through referrals of known employees. Therefore, having a solid network of people working in data science is an asset. 

7. Having a mentor to  support your data science career

An impactful way to choose the right strategy to land a data science job in the most coveted data science organizations or even build a solid network is by having a mentor to guide and support you. Seekho offers exclusive mentorship to accelerate your data science career. 

8. Working for growing companies

Search for data science jobs is often an uphill task. Individuals aim for top organizations that rarely hire people without real-world data science experience. Starting your career with a growing company is always advisable since the learning and growth curve are steep. Also, since you are out there in the data science world, it is easier for your dream organization to identify you based on your exceptional data science work. 

Conclusion

To conclude, according to the latest WEF report, data science jobs will be the most in-demand by 2025. Moreover, the number of data science jobs will continue to rise in the coming years. A well thought and executed action plan will help you find your dream job and be the next big move of your career.  

If you want to accelerate your career and be a part of this data science revolution, join the ‘Seekho Select Membership.’ Seekho Select Membership helps you get closer to the most exciting jobs and internships. Seekho through 1000+ live classes directly from industry experts. With Seekho, you become an integral part of a learning community that’s always there for each other. You also get exclusive mentorship via live classes, breakout sessions, and discussion forums.

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