By Damien Tanner
According to Fortune, data scientist roles are projected to grow by 36% from 2021 to 2031. Further, it’s expected that these jobs will involve greater specialization in the years ahead.
For both of those reasons and more, now is a great time to launch your career as a data scientist. At AI/ML Jobs, we know that starting a new career in the industry can be difficult.
However, with our easy-to-use AI and machine learning jobs board, you can browse through a wide range of opportunities, including entry-level data scientist roles!
In this article, we’ll be discussing the various types of data scientist roles, why you’ll want to consider a career as a data scientist, and how you can get started.
Let’s dive in!
A data scientist collects, analyzes, and interprets detailed digital data to support various business decisions while using a scientific approach.
A data scientist’s role may include:
| Company | Average Total Pay |
| Apple | $198,447 |
| Microsoft | $186,997 |
| IBM | $155,869 |
| $264,719 | |
| Meta | $312,813 |
So, how exactly do you become a data scientist? In general, you need to take four career steps from entering the industry as a Junior data scientist to becoming a Data Science Manager.
The entry-level role on this career path is that of a Junior data scientist. This is a person with 0 to 2 years of data science experience. But how can you land a role like this without any experience? It will certainly help to have a relevant degree (and the same applies to all jobs along this career path).
Junior data scientist work tends to involve:
With three to five years of relevant experience, you may prove eligible to become a mid-level data scientist. Naturally, the work involved in this role is more complex.
Also, rather than solving particular issues, a mid-level data scientist is more likely to work on exploratory data analysis. This can involve discovering hidden patterns in the data to aid in the company’s overall strategy.
Some tasks of a mid-level data scientist can include:
Higher up still is the role of a Senior data scientist, who will use data analysis to improve business development and company strategies. While similar in some ways to a Junior data scientist, a senior professional will have more responsibilities and authority when it comes to long-term decision-making based on data analysis.
Examples of Senior data scientist tasks are:
Lastly, those with at least five years of experience in a similar role may be capable of taking on a data science manager role. In many cases, you’ll need at least 1–3 years of supervisory experience to land this sort of job.
Data science managers hold the top position in this field within any given business and hold significant responsibility to support the company’s long-term objectives.
Data science manager tasks will include:
If you’re not sure exactly what area in IT appeals the most to you with regard to career prospects, here are some of the best reasons to go down the route of being a data scientist.
The job market for data scientists is on the rise. In fact, according to the U.S. Bureau of Labor Statistics, related work prospects will grow by 15% between now and 2029. All in all, becoming a data scientist is a great way to kick-start a promising career with tons of opportunities.
The data science field is ripe with opportunities for professional growth and development—both vertical and horizontal. As a data scientist, you can move up the ladder in your current organization or choose to work in different organizations with slightly more challenging roles and responsibilities.
According to Glassdoor, the average base salary for a data scientist is $103,865 per year.
However, with additional pay of $22,700, the average total annual salary for this role is $126,565. Glassdoor also claims that the “most likely range” for the total pay lands between $98,000 and $164,000.
If you’re keen to become a data scientist, you may be wondering how to get your foot in the door. Here, we’ll explore a step-by-step breakdown of how you can land your first role as a data scientist.
Most data scientists’ roles require at least a bachelor’s degree in a relevant field (e.g., data science or computer science). That said, it’s even better to have a master’s degree in a related field. Additional data science certifications (e.g., boot camps, intensives, short courses, etc.) are a great way to flash out your resume.
Along with expanding your knowledge and gathering accreditation, developing a strong skill set is critical to giving you the best chances of launching a data scientist career when the time is right.
Along with the skills you’ll develop through education, you may want to add the following skills to enhance your general IT aptitude:
Developing your own data science projects can not only further your skills and knowledge, but will look great on your resume.
Project types you may want to consider with regard to a data science approach include:
Some projects will better suit your existing skills and knowledge than others. Naturally, you’ll want to highlight the projects that are most relevant on your resume, based on the value of the experience and whether it was undertaken at an opportune time—when you had the expertise to succeed.
Increasing your profile and growing your network are also key to kick-starting your career as a data scientist.
As mentioned, a suitable data science project can help raise your profile. Obviously, to add weight to your name, you’ll want to effectively communicate to your network and potential employers the value and findings of your project(s).
Some ways of highlighting the success of your project(s) are:
After you’ve gathered the necessary skills, certifications, and experience, it’s time to apply for entry-level data scientist roles.
When applying, be sure to consider what employers appeal to you most in terms of pay, perks, and the quality/culture of the company.
After all, if you plan to work in a particular business for at least several years, you’ll want it to be a good fit for your career goals, values, and work mindset. From there, you can start your journey, working toward higher positions over time.
If you’re ready, why not look for suitable employers today? AI/ML Jobs is the number one place to browse thousands of AI and machine learning jobs from across the US and the wider world. Use our services to search for jobs based on location, skills, and salaries!
In this guide, we’ve explored the career path of a data scientist in the modern IT industry. We’ve looked at the types of jobs available, why you might want to consider one of these roles, and how you can become a data scientist.
Visit AI/ML Jobs today and explore a range of industry jobs including data scientist roles. Use our service to look at the top jobs in terms of location, skills, and salaries!