The world, specifically the virtual world, is overflowing with data; reports show that over 90% of today’s data has been generated in the last few years, and it shows no signs of slowing down as predictions made see the data reaching 175 zettabytes by 2025. It is fascinating to witness the development of various career options related to data and ways to use all that information to improve decision-making and industries in general, with data science being one of the most popular options.
If you are interested in pursuing a career that is as challenging as it is rewarding, look no further! Becoming a data scientist is an excellent career choice, so read on as we tackle all there is to know about this profession and, more specifically, how to get a data science job.
Becoming a Data Scientist
Once people decide to consider a future in data science, they typically have two questions:
- How to become a data scientist?
- What skills are needed to be a data scientist?
Although each person’s journey toward success is different, most, if not all, data scientists succeed by obtaining the necessary skills and knowledge in the field through formal education.
Education
Typically, the minimum level of education required for data science professionals is a bachelor’s degree in computer science, data science, or another related field. Still, we advise you to continue updating and upgrading your knowledge as well as skill set by furthering your education and pursuing a master’s degree in data science or another discipline related to it. After all, with a higher level of education, you also increase your chances for better career opportunities and an increase in salary over time.
Skills
To become a data scientist, you need to obtain a number of technical and non-technical skills that allow you to properly deal with your daily responsibilities and duties. Some of the technical skills needed for the job include:
- Knowledge of statistical analysis and computing
- Ability to process large amounts of data sets
- Data visualization
- Machine Learning and AI
- Deep Learning
- Mathematics
- R Programming
- Python coding
On the other hand, in order to have the required mentality and ability to work well within a team of data scientists and other data-related professionals, as well as learn to automate data entry, you need to obtain and develop the following soft skills:
- Communication
- Critical thinking
- Collaboration
- Business acumen
- Adaptability
- Problem-solving
- Data intuition
- Intellectual curiosity
How To Get a Data Science Job
Suppose you have completed your studies and obtained the skills needed for the job. What then? How should you find suitable opportunities and secure the desired job positions? Well, there are a few steps you must go through in order to find jobs you can apply for and present the best possible version of yourself to potential employers.
Build a portfolio
Firstly, it is essential to have a portfolio that documents your work experience and capabilities in the field of data science. Such a portfolio acts as a collection of your best work and demonstrates your skills in the data science field. You should include a combination of any relevant code you have written, writing samples that show your abilities to effectively communicate with others regarding data, and other appropriate documentation.
Create an outstanding resume
Although it is easy to create a resume and send that same one to each job you apply for, if you want to have a better chance of getting an interview, you must create customized resumes for each position. You can do so by highlighting all the relevant skills and job experience that mirror the job description provided.
To create an outstanding resume, you must include the following information:
- Name
- Phone number
- Portfolio
- LinkedIn or other relevant profiles
- List post-secondary degrees (Ensure to include the year of graduation)
- If applicable, mention certifications you have completed, online courses in data science, or other relevant subjects
- Previous job experience (Make sure to list everything in reverse chronological order)
- Additional information on the industry and roles you have worked in
- If applicable, add accomplishments like awards
- Mention all relevant skills (specifically ones the job description demands)
Network
The next step is to network and create valuable connections that will help you find and secure job opportunities.
You probably heard the saying, “Who you know is more important than what you know.” Well, that is the ideology behind networking, and it has proven to be a successful approach. Reports show that around 85% of jobs are found through networking, and about 79% of professionals believe that career success depends on the connections they have created with other professionals.
Nowadays, it is easier than ever to network since universities, in particular, provide sufficient opportunities for you to meet and create connections with other professionals, whether they be other students, professors, alumni, teaching assistants, or other professionals in the field. Attending networking events and conferences related to data science or simply speaking to your professors about the market of data science will provide you with better opportunities within the field.
Find a mentor
We all need help and guidance sometimes. So, an excellent tip for anyone joining the data science field is to find a mentor that can provide foundational social capital for you as you begin your career, help guide various project works, and offer professional advice. Look for a mentor, like a professor or another professional in the field of data science, who can leverage their expertise and experience to guide you. Such a professional can help you grow—professionally and personally—make better decisions, and gain insight into data science.
Prepare for your interviews
If all other steps go well, you will quickly find and apply for a job in the data science field. Once you secure an interview, you should be well prepared to wow the hiring manager and secure the job. Do extensive research on the company you are interviewing for as well as the role—employers love hiring people who are well-informed about their objectives and eager to join the team.
Then, review your portfolio and overall resume, paying close attention to all the skills and experiences listed in case you are questioned or tested about any of them. We would advise you to do mock interviews with your mentor or a friend so you feel comfortable answering questions related to the data science field. This way, you will feel better prepared, more confident, and less stressed about interviewing for the job that can decide your professional future.
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Where To Look For Data Science Jobs
We already mentioned that one way to look for and find available data science job positions is through your networking links. However, there are other ways to hunt for a job, including using technology. The online world has made finding suitable employment in any domain reasonably easy. Various online websites have millions of job listings available for you to explore, including thousands of positions in data science. You can look through sites such as:
These sites have features that help you narrow your search according to the exact role you desire, the company you want to work for, the location, salary, and other factors that interest you as you look for data science jobs.
3 Entry-Level Data Science Jobs
Though we have repeatedly mentioned that whether it be to create a portfolio or an outstanding resume, you need relevant job experience in data science, you do not necessarily need to have worked prior to applying for a job in the field. So, how to get a data science job without experience? Well, begin small and apply for entry-level data science jobs that help you receive on-the-job training, which later turns into the experience you refer to when you apply for higher-level data science jobs. Below, we have listed three popular choices for entry-level employment in the data science field.
Junior data scientist
One of the top entry-level positions aspiring data scientists pursue is that of a junior data scientist. Such a role is relatively new to the data science field and is primarily concerned with collecting, analyzing, and presenting data that other teams within the organization use. Their responsibilities are similar to those of a senior data scientist; however, the main difference is that they typically work on less critical projects.
To succeed in this role, you must understand the fundamentals of statistics and have relevant computer skills, including the ability to work with various programming languages and databases. The exact skills needed for the role may depend on the company you work for.
Junior data engineer
The next role you could apply for is that of a junior data engineer. Such positions are typically available part-time and full-time, depending on whether you have recently graduated or are continuing your studies and can dedicate only some of your time to the role.
When working as a junior data engineer, you must thoroughly understand the technical side of data, specifically how it is gathered, stored within the software, and analyzed. Once again, the duties and responsibilities of this entry-level role are similar to those of senior positions. However, such professionals are usually found working on smaller projects that don’t have much impact on the company.
Junior data analyst
Junior data analysts, like the previously mentioned roles, have obtained the basic skills and knowledge required for working in data science and data analysis; however, they are still learning how to apply themselves in a professional setting.
You will be required to manage and analyze big data using various tools under the guidance of more experienced professionals. You will work with other data scientists, analysts, and engineers as you help them with their projects by cleaning up data they can use.
Data Science Job Outlook and Salary
When comparing the amount of data created daily (roughly 2.5 quintillion bytes per day) with the small number of people working as data scientists (a little over 3000 data scientists in the United States), there is always a demand for such professionals in the labor market. In fact, various lists of the best jobs with guaranteed future growth and high-paying career options include data scientists in them.
According to the Bureau of Labor Statistics, employment of data scientists in the United States is projected to experience a 36% growth from 2021 to 2031. This percentage is much higher than the average for all other occupations, as around 13,500 new job openings are expected each year throughout the decade. Similarly, the salary associated with the profession is satisfactory too. Recent reports show that the average salary of data scientists in the United States is $102,906 annually. However, the exact figures depend on the role, company, location, experience, and other factors.
Conclusion
Many industries have already accepted that in order to be successful, they must make the most of the millions of bytes they gather daily. To use all these data sets, they need people like you—ready and willing to obtain the theoretical knowledge and skills required to make sense of data and transform it into valuable information. So, start your data science journey and take your first steps towards a career filled with success.