Data science is a popular field with a growing number of people exploring whether a career in this industry is a good move. While there are many benefits to a data science career, there are also many challenges to consider when weighing the costs and benefits of working in data science. Whether you are interested in a new career, a career transition, or simply upskilling to advance your current career, there are a few questions to consider before deciding if a data science career is right for you!
Questions to Consider When Choosing a Data Science Career
1. What Are the Costs and Benefits of a Data Science Career?
Before considering whether or not you want to pursue a career in data science, it’s important to have a deeper understanding of the industry and weigh the costs and the benefits of a data science career. Let’s start with the benefits. Data science is a fast-growing field with many new opportunities for growth and development over the coming decades, especially in the areas of big data, machine learning, and artificial intelligence. Many newly-learned data science skills are highly transferable to multiple positions and employment opportunities in a range of industries.
Data science is a skills-based industry, and one of the big costs of pursuing such a career is the time required to develop technical skills. In addition, harmful myths about learning data science skills create fears about being able to apply one’s skills to real-world problems or in a workplace environment, causing many people to decide against pursuing a data science career. Another drawback is that as data science becomes more popular, more people transition into the industry, having learned top data science skills, and competition in the field increases. So, more experience and more niche skills may be required to stay ahead in this ever-evolving industry.
2. What is Your Industry of Interest?
After a cost-benefit analysis, your next determination is what industry interests you and is your preferred industry hiring data scientists? Many industries naturally rely on data science, and many unexpected industries have transitioned into prioritizing data. So, this is the perfect time to break into a new industry or upskill in your current one. You should also determine if your interest in data science stems from your current field becoming more data-focused or if you are looking for a path to a different field.
Your knowledge, experience, and current industry will determine if transitioning into a more data-focused career might simply require learning additional data science tools or skills, perhaps with an interest in what data collection and analysis looks like in your field. But if your career goals lie with an industry that is a big departure from your current career, read on to the third question that you should ask yourself.
3. How Much Time/Resources Can You Devote to Data Science?
After choosing an industry of interest, you must ask yourself, “How much time and resources can I devote to data science?” Time and cost depend on your background and experience and the type of industry or career that you wish to pursue. Learning data science skills requires varying amounts of time and finances, in both the short and long term. For example, some data science careers require a college degree, which can take several years and tens of thousands of dollars while also requiring in-person instruction. In comparison, data science bootcamps can be completed in a few weeks in an online learning environment for significantly lower upfront costs.
Most data scientists begin their careers with entry-level positions in data analytics, moving up to more responsibility and eventually management concurrent with growing experience. It is crucial to lay out a clear path toward your goals. This includes assessing where you are in your current career, whether you can commit to the time and cost required at the outset, or if you want to pursue a more lateral move (which would require learning more skills with the training and costs spread out over time). Only you can determine how much money and time you can commit to pursuing a data science career, and whether it will be worth that cost in the long run.
4. What is Your Background and Skill Set?
The time and resources necessary for a career in data science are also influenced by your background and skills. Consider the following questions: To what extent do your current experience and career path align with the data science industry? Can the skills you’ve learned and developed in your current position translate into a data science career?
For example, work in a STEM field or a position that requires some mastery of data science projects and tools. You have a better understanding of what it takes to pursue a data science career than someone with a background and skill set unrelated to science, technology, mathematics, and engineering. If your professional background is unrelated to data science, it’s a good idea to learn about the field to determine if it is right for you. There are multiple data science internships and freely available seminars and workshops that offer hands-on experience in developing data science skills and projects.
5. Are You a Lifelong Learner?
Like all STEM fields, data science is in constant flux like all STEM fields, so the final questions to consider are: Are you passionate about learning new things, i.e., are you a lifelong learner? Are you interested in keeping pace with trends in the data science industry? Are you eager to keep your skills relevant by taking advantage of regularly-occurring training opportunities?
The answers to these questions also play a part in your cost-benefit analysis. If you are not passionate about learning new things or keeping up with training for the technical skills or tools required, a data science career may not be a good fit. However, it is a great fit for lifelong learners excited about working in an industry that continues to change and develop because it offers multiple opportunities to learn new skills and take on more challenging responsibilities through complex problem solving and project development.
Is a Data Science Career Right for You?
Honestly answering the preceding questions is a useful way to determine whether or not a data science career is right for you. If your answer is “Yes, ” then it’s time to explore Noble Desktop’s extensive portfolio of data science classes and certificates, to learn more about the skills required for a career in the data science industry. For example, the Data Science Certificatecourse includes training in Python and SQL programming languages, with a focus on machine learning and database management. In addition, the Data Analytics Certificate offers training in predictive and prescriptive analytics through hands-on experience with information technologies and business intelligence tools.