Data Science

6 Tips To Help You Land A Job In Data Science

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14.07.2021

Job hunting in the present time has become challenging as well as time-consuming for many graduates. Universities and middle colleges are churning out thousands of graduates in many career fields. However, with the right strategies, you can stand out from the crowds and get yourself hired by the best employers on the globe.

Why Demand For Data Science Is Growing

Among the highly sought-after professionals are experts in data science. It’s projected that job openings for data science are bound to grow by at least 50% in the next few years. The growth in demand for these professionals is attributed to:

  • More organizations are becoming data-driven, which in turn, increases their ROI especially for those that are investing in analytics. This helps such companies cut costs.
  • You can do data science jobs from home. This saves employers costs of office space.
  • Due to the outbreak of the COVID-19, companies are making use of data scientists to monitor the behavior of the pandemic, project market trends, and come up with new simulations and models to create opportunities for recovery.

So, to give you a good head start, whether you’re a fresh graduate from college, or are seeking greener pastures, here are some tips that can help you land a job in data science:

1. Market Yourself Online

If you want to market yourself in the best fashion possible, the best starting point is your Resume. Your resume needs to reflect everything good about you. This means all your past professional experience, educational qualifications, and any detail that can help your case. Working with an experienced platform like Arc Resumes can help you create a resume that will be professional and help attract the right kind of attention from employers.

COVID-19 has deconstructed the traditional strategy that employers have been using in recruitment processes. The requirement for social distancing is shifting many recruiters to virtual employer branding, assessment tools, and outreach. Because of this, you should create your presence in the following areas:

  • LinkedIn: Many employers are carrying out employee searches on LinkedIn especially during the pandemic. Ensure that your LinkedIn profile is updated with your current skills and courses to level up your employability. The first thing the employer will see is your profile picture, which creates the first impression. Upload a professional image, write a bio optimized with relevant SEO keywords, and something that encapsulates your prior experiences. To increase your chances of getting seen on this platform, you can study more data analyst resume LinkedIn tips and look into some templates that can help you build your online resume.
  • Update Your Portfolio On Other Online Platforms: For an outstanding data science resume, take time to do industry research, adopt a visually attractive format, list all your relevant experiences and technical skills. Place this information on your website. You can also create a GitHub portfolio showcasing recent projects you’ve accomplished.

2. Add More Skills

While your college degree will suffice, you can increase your chances of getting hired by gaining more data skills through online courses. For applicants in the field of data science, employers typically prefer those with a degree in computer science, statistics, applied mathematics, economics, or other related courses.

However, during interviews, most employers go for candidates with more skills and experience over ones with countless degrees. Take advantage of the setup you have now and earn yourself more certifications. You can earn the following skills by studying data science:

  • Programming Skills: The highly preferred languages in data science are Python, R, C++, Hadoop, and Java. Knowing a scripting language is also an added advantage.
  • Data Skills: You’ll need skills in data management, data manipulation, and data visualization. Learning Structured Query Language (SQL) enables you to understand the relationship between large data sets, while other applications such as Power BI and Tableau can help you present data simply and understandably.
  • Machine Learning Skills: Machine learning is a higher level of data science for bigger data that employs both supervised and unsupervised algorithms, including reinforcement learning.

3. Network With Other Professionals

Maintain your relationships and connections with your coursemates or even other professionals who have been in the data science field for a long time. Through this, you can land yourself good referrals or stay updated on opportunities around.

Many times, the real challenge is securing your first entry-level job. Therefore, having a web of good connections can work miracles for you. Networking may not yield an immediate outcome, but it can be extremely helpful in the long run. To increase your network, attend the right events and reach out to individuals working in your company of interest.

4. Choose A Suitable Role

Many professionals in this field deal with business data. Thus, you need to ensure that the role you’re applying for matches your skills. Understand that data analysts, data scientists, machine learning engineers, and data engineers are different from data scientists.

Large technology companies require further specialization, which is done internally after the recruitment of new graduates or interns. Top global companies that give amazing opportunities to data scientists include Pinterest, Facebook, Lyft, and Uber. You can also become a freelance data analyst and have flexible work schedules.

5. Work On Your Communication Skills

Not many people think that communication skills are critical for individuals pursuing a data science career. They tend to think that their prowess in technicalities is good enough to get into the job market. Well, remember that you have interviews to attend, and this is what usually edges away many data science job seekers.

Moreover, you’ll need communication skills during your company meetings for presentations and discussions with your colleagues.

6. Have A Mentor

Having someone who is more experienced in the field can be very helpful for starters. There are relatively few individuals who have conquered the field of data science. Ask your mentor how they’ve come this far in the field. They can also guide you on the right professional courses to enroll in, as well as the role that suits you in the data science field.

A mentor is also critical in knowing the important events to attend for your networking efforts. Finally, a mentor can give you referrals that you would not have found on your own.

Bottom Line

Data management is a critical thing in many companies especially telecommunication companies, social media companies, among others. According to the requirements of most companies, you have to possess excellent knowledge in programming languages such a Python, C++, and R. Good skills in scripting languages will also be an added advantage for you.

Create a solid online presence to enhance your visibility, look for a mentor to guide you, optimize your website and social media accounts, and keep on learning how to level up your resume. Applying these tips when hunting for your data scientist job may help you reap amazing results in the future.

Read Also:

Tags data science internship data science interview questions data science projects ibm data science professional certificate towards data science
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Mashum Mollah is an entrepreneur, founder and CEO at Viacon, a digital marketing agency that drive visibility, engagement, and proven results. He blogs at BloggerOutreach.io.

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