Are you interested in transitioning into a career as a data analyst from another profession? Are you already in an entry-level position and wondering what comes next? Regardless of where you are right now, if you think that data analytics is the career for you, it can be a good idea to familiarize yourself with the typical career path.
Below, we highlight the duties commonly associated with the role of a data analyst, review key career paths, and offer advice that you can use to advance your career.
What do data analysts do?
Ultimately, the specific responsibilities of a data analyst can vary dramatically depending on a number of factors. The industry that an analyst works within, the company that employs them, and even the size of the team can all dictate what the role looks like.
In the broadest sense, however, data analysts are involved in collecting, analyzing, and interpreting data as it pertains to an organization. Some of the most common responsibilities of a data analyst include:
- Designing and maintaining data systems and databases as necessary
- Troubleshooting and fixing errors in the code that keeps these databases working
- Mining data from primary and secondary sources
- Cleaning and organizing raw data into a usable form
- Interpreting data sets by leveraging a number of statistical tools
- Preparing reports for internal stakeholders
- Collaborating with other members of the data team, including data scientists, data engineers, and analytics engineers
Data Analytics Career Paths
According to Uwe Hohgrawe—assistant teaching professor and lead faculty member for the Master of Professional Studies in Analytics program within Northeastern’s College of Professional Studies—the specific job titles that an individual might hold throughout their career as a data analyst can vary substantially.
“It depends also on the background and the domain interest that people have,” Hohgrawe says. “You have analysts working in marketing and finance, for example, and they have titles like marketing analyst, financial analyst, HR analyst, etc.”
Hohgrawe also notes that many professionals may perform analytics work without holding a title that has the word “analyst” in it. Marketing specialists or HR managers, for instance, often perform a significant amount of analytics work as part of their daily duties. Additionally, those who are in junior analytics roles may not see “analyst” added to their title until they advance. “In every incidence lies both a great opportunity for upskilling,” Hohgrawe says.
Below is a brief list of some of the most common career paths that data analysts pursue. For each of these roles, it is not uncommon to find job titles appended with the words “junior,” “senior,” “manager,” or “director” as a means of signifying the level of seniority.
- Business analysts work to analyze data related to their specific business or organization, as well as the industry that they operate within.
- Budget analysts are responsible for preparing budgets, monitoring spending, and otherwise organizing and reporting on the finances of the organization.
- Compensation and benefits analysts are typically a part of the broader human resources (HR) team. They conduct analysis to inform compensation packages, and may also be concerned with metrics such as employee turnover.
- Corporate strategy analysts conduct an analysis of the organization’s broader corporate strategy in order to make recommendations that guide key decisions. They’re often involved in mergers and acquisitions.
- Marketing analysts analyze the organization’s various marketing channels in order to identify areas of strength and weakness.
- Product analysts focus their efforts on specific products or product lines, determining the characteristics that consumers expect and desire in a product as well as advising on factors such as pricing.
- Sales analysts regularly analyze an organization’s sales activities, including their volume of sales and the shape of their overall sales pipeline, in order to better support and optimize the sales team.
In addition to the most common titles explored above, there are many other career paths for data analysts. Insurance underwriting analysts, actuaries, and fraud analytics are all often employed by insurance companies, for example. Meanwhile, credit analysts are often employed by banks and financial institutions, while web analysts and social media analysts often work within a marketing team.
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Advancing Your Analytics Career
Regardless of the specific industry or specialty you pursue, Hohgrawe notes that the path toward advancing in your career will largely be the same. As such, following the steps below can help you more effectively move from entry-level to more senior positions.
1. Grow your network.
One of the easiest of actions you can take to help your career also happens to be one of the most impactful: Growing and staying involved in your network.
“You, as an individual, need to be aware of what’s happening around you in your professional field and in other companies and organizations in your domain,” Hohgrawe says.
The people who make up your network might notify you about potential career opportunities such as open positions at new companies, but this isn’t the only benefit of engaging with these professionals. Staying involved in your network also allows you to learn how others have tackled problems that may also impact your organization. This knowledge empowers you to demonstrate value at your current organization, which, in turn, can make advancement more likely.
2. Develop your skills.
In analytics, as in other technical fields, career advancement is often tied at least in part to the specific skills and expertise that you bring to the table. Therefore, one of the surest ways of advancing in your career is to continuously develop new skills that you can put into action while completing your day-to-day duties.
Though the specific skills that will best suit you for your career will vary, some of the most in-demand analytics skills include:
- SQL
- Tableau
- R or Python
- Statistics
- Data Visualization and Communication
- Business Intelligence
- Machine Learning
How exactly you choose to grow your skills will be dependent on how you learn best. While some may find that they can effectively expand their skill sets on their own by reading books or articles, watching videos, or conducting their own independent research, other students may find value in the structure provided by formal, skill-focused education. An analytics bootcamp, for example, may be an effective means of learning a specific tool or practice in a condensed amount of time.
Another potential option noted by Hohgrawe is to pursue something called a “badge” or “micro-credential” from a university. While the specific form that a “badge” will take depends on the university, these are often aligned to a very specific skill or subject area and offer students a means of very quickly learning something that they can put into practice.
For example, Northeastern University’s College of Professional Studies currently offers a number of badges that interested students can enroll in to learn about topics ranging from leading remote teams to data literacy to leadership. Hohgrawe notes that a number of these badges are directly relevant to individuals interested in breaking into the field of analytics, including:
- Stats for Starters
- Data Literacy Fundamentals
- Analytical Thinking
- AI Readiness
- Exploring Python
“Badges are a great way to get a taste of different concepts in analytics, such as statistics, data visualization, data literacy, etc.,” Hohgrawe says.
3. Pursue a graduate education.
Finally, Hohgrawe notes that pursuing graduate education in the form of a graduate certificate in applied analytics or master’s degree in analytics can often be one of the most successful ways of advancing in your career as a data analyst.
This is because, in addition to helping you develop new skills and expertise that you can leverage in your career, a graduate degree is a form of differentiation between you and others who may be applying for the same job. In fact, many employers have even begun to require that applicants hold an advanced degree even to be considered for a position—particularly for more senior-level roles.
Taking the Next Step in Your Analytics Career
If you are looking for a way of advancing in your analytics career, earning a Certificate in Applied Analytics or a Master of Professional Studies in Analytics from the College of Professional Studies at Northeastern can help you achieve just that.
“What we do at Northeastern is we teach the three literacies of data, technology, and humanics (the humanities, communication, and design),” Hohgrawe says. “And so that combination of the three, if applied right, makes the difference between a good and an excellent analyst.”
The result is that students who complete the degree graduate with the data and technical skills that employers are looking for, in addition to other skills like business intelligence that make for a well-rounded employee.
This education goes beyond theory and academics, however. Co-ops at organizations ranging from start-ups to industry-leading corporations give students the ability to put their education into action and gain actual experience—which can help you stand out from the competition.
Learn More: Co-op vs. Internship: What’s the Difference?
“Our program offers a lot of very exciting experiential learning opportunities,” Hohgrawe says. “This helps you as a student to learn how to apply data literacy to manage the flow of big data, technological literacy to know how machines work, and the human literacy in an analytics project.”
At the same time, you’ll be building valuable connections with your classmates, faculty, and more than 255,000 alumni and 3,350 employer partners, helping you grow your professional network into a tool that can help you advance through your career.
Learn more about advancing your career with a Master of Professional Studies in Analytics from Northeastern.
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