Top 5 Tips to Land a Job in Data Science in 2021

Over the last few years, the field of data science has become one of the most sought-after fields for hiring managers as well as job-seekers around the world. LinkedIn ranked having a job in data science as the most promising career for the year 2020. This was based primarily on the salary projections as well as a near 61% increase for job openings from 2019. Data scientists clean and collect massive amounts of data. Moreover, they maintain easy-to-use databases and dashboards and interpret data for the purpose of solving problems. They also build algorithms, run experiments and provide data to potential stakeholders in various highly attractive visualizations. In the modern era, there have been various reasons for pursuing a career in the field of data science. Some of the reasons include a high salary, relatively stable and growing job market even during a global recession. As a result, there are exciting problems for solving across various diverse industries across the world. In this article, we would provide you five tips for landing a job in data science in the year 2021.

Improve your math skills

If you belong to a quantitative background, job in data science could prove to be a fairly easy transition for you. Before you focus on analyzing data through the means of high-tech tools, you should focus on making a strong foundation for data analysis. This could starts with plotting data points on graphs throughout the X and Y axes along with finding trends and correlations across different variables. For the purpose of making sure that you are able to write highly efficient code along with providing accurate conclusions, you should focus on having a strong grip on some important mathematical concepts. These concepts include probability distribution, statistical methods and probability theory, linear algebra, probability distributions, multivariable calculus, hypothesis testing, statistical modeling and fitting, regression analysis, data summaries and descriptive statistics.

Learn a programming language

When compared with various other career fields, data science focuses more on what you already know and how well you are able to prove your specific skillset and less on the prestige of your individual alma mater. The process of having a skill-based interview focuses on giving a level to the playing field for individuals that are coming from different backgrounds. If you build a strong foundation with math, you will also be able to start a few of the must-known programming languages for aspiring data scientists. They may include but are not limited to SQL, R, Python, and SAS.

Take on internships or side gigs

For the purpose of creating your resume, organizations will require professional practical experience. When you start building out your knowledge, you will be able to apply your individual skill-set across real-world settings. This will also help you to obtain real-time feedback as a professional. You can also utilize freelancing platforms that may include Upwork or Fiverr. Moreover, you can also make a search for internships or part-time work by the means of social media and job boards. Kaggle provides competitions with monetary prizes. Before giving an interview, you should be able to make sure on practicing coding problems and also explore potential data science interview questions.

Update your LinkedIn profile and personal resume:

Recruiters across the world have been actively utilizing LinkedIn as a prospective search tool so that they can find promising candidates during COVID-19. Recruiters spend a significant time on LinkedIn profile photos. As a result, you should select a professional image. Moreover, you should also provide a detailed summary section that should be optimized for SEO keywords. Apart from that, you should also make sure that your past work experience has also been clearly presented and is up-to-date. You should update your personal resume along with other online portfolios and personal websites. For the purpose of crafting a compelling data science CV for yourself, you should be able to remember that recruiters across the world have been looking for a first impression. You should conduct comprehensive industry research and identify essential keywords in your descriptions for a job in data science. You can also select a visually appealing format along with providing your individual experience along with various other technical skills. It is essential that you are able to make sure that you can effectively quantify your personal influence.

Brushing up on personal interviewing skills:

Organizations across the world are quickly adopting virtual interviews to replace personal interviews. For becoming successful in interviewing through the means of Zoom, Google Hangouts, Blue Jeans, or other platforms, the Society of Human Resource Managers (SHRM) recommends cross verifying your technology (camera, microphone, and Internet speed). You can also select a quiet room and can also make sure that you have adjusted your calendar for different time zones. Set up practice sessions, so that your personality shines through in the behavior/fit portion of the interview.