4 Data Analyst Career Paths: Your Guide to Leveling Up

Getting a job as a data analyst is the first step in what could be a larger, in-demand data career. After you've gained experience as a data analyst, you have a few different options to consider. In this article, we'll take a closer look at four common career paths you can explore to first get started and later advance.

If you're ready to jump in right away, consider enrolling in the Meta Data Analyst Professional Certificate. Over five courses, you'll learn a variety of key skills, including how to collect, clean, sort, evaluate, and visualize data.

Getting started: Entry-level data analyst jobs

If you’re new to the field of data analysis, your first job might be an entry-level role as a junior analyst. If you have some experience with transferable analytical skills from a previous job, you may be able to get hired as a data analyst.

Before applying for that first job, you’ll want to develop some core data analyst skills, including SQL, R or Python, data management, statistical analysis, and data visualization. You can practice statistical analysis, data management, and programming using SQL, Tableau, and Python in Meta's beginner-friendly Data Analyst Professional Certificate. Designed to prepare you for an entry-level role, this self-paced program can be completed in just 5 months.

Read more about how to become a data analyst, even if you don't have previous experience or a degree.

Leveling up: Four career paths for a data analyst

As you gain experience as a data analyst, you may encounter opportunities to advance your career in a few different directions. Depending on your goals and interests, you may progress into data science, management, consulting, or a more specialized data role. 

Let's take a closer look at four possible career paths you might take in the world of data.

1. Data scientist

Many data scientists start out as data analysts. Making this transition typically involves:

• Advancing your programming skills

• Learning more advanced mathematics

• Developing an understanding of machine learning 

Many data scientists also have a degree in data science, computer science, or a related field. While a degree may not be strictly necessary, having one can mean more job opportunities.  

Read more: Data Analyst vs. Data Scientist: What’s the Difference?

2. Management

Another common career path for data analysts is to move into management positions. You might start out as a data analyst before advancing to senior-level analyst, analytics manager, director of analytics, or even chief data officer (CDO).

If you’re interested in pursuing this path, you’ll want to focus on developing your leadership skills alongside your data skills. In some companies, a master’s degree in data analytics or business administration with a focus on data analytics might be required to attain these higher-level positions.

3. Specialist

As a data analyst, you might work in one of many different industries. Sometimes, your career path might take you deeper into the specialized knowledge of that industry.

• Business analysts use data to help make an organization’s IT processes, organizational structures, or staff development more efficient and effective.

• Financial analysts use data to help guide investment opportunities, identify revenue opportunities, and mitigate financial risk.

• Operations analysts are tasked with optimizing a company’s performance by identifying and solving technical, structural, and procedural issues.

• Marketing analysts, also called market research analysts, analyze market trends to help determine product and service offerings, price points, and target customers.

• Systems analysts use cost-benefit analysis to help match technological solutions to company needs.

• Health care analysts use data from health records, cost reports, and patient surveys to help providers improve their quality of care.

4. Consultant

Once you’ve gained several years of experience analyzing data for a company (or several different companies), you can consider working as a data analytics consultant. Instead of working for a company directly, you’d work as a freelance contractor or for a consulting firm, conducting analysis for a variety of clients.

Working as a consultant often means more variety in the type of analysis you’re performing, as well as greater flexibility (particularly if you’re self-employed).

How much can you make? Data analyst salaries by role

Even entry-level data analyst positions tend to be well-paid. As you add years of experience and advanced job titles, salaries often go up accordingly. Here’s a quick look at the average base pay of different data analyst roles in the US in October 2023, according to Glassdoor:

• Junior analyst: $61,807

• Data analyst: $71,993

• Senior data analyst: $95,902

• Analytics manager: $126,541

• Director of analytics: $168,145

• Chief data officer (CDO): $183,481

• Data scientist: $111,315

• Business analyst: $79,069

• Financial analyst: $71,610

• Operations analyst: $58,649

• Marketing analyst: $68,822

• Systems analyst: $90,781

• Health care analyst: $70,385

• Data analyst consultant: $89,631

Build your data analytics career on Coursera

Whether you're interested in getting started in data analytics or advancing your skills, you'll find an array of programs suited to your experience level on Coursera. We've outlined several options below.

• Take the first step toward a career in data analytics with the Meta Data Analytics Professional Certificate, available on Coursera. Build job-ready skills over five courses. Upon completion, you'll have an employer-recognized certificate and a portfolio to showcase your work.

• Improve your ability to work with key tools such as Microsoft Excel and Microsoft Copilot with the Microsoft Excel Professional Certificate. You'll learn how to navigate the Excel interface, apply essential formulas, and effectively use Copilot for tasks, queries, and data manipulation

• Explore business analytics with the Microsoft Power BI Data Analyst Professional Certificate. Learn how to drive data-driven decision-making and prepare for the industry-recognized Microsoft PL-300 Certification exam. Plus, learners who complete this program will receive a 50% discount voucher to take the PL-300 Certification Exam.

• Advance your data career with DeepLearning.AI's Data Engineering Professional Certificate for intermediate learners. You'll build skills in the five stages of the data engineering lifecycle, including generating, ingesting, storing, transforming, and serving data.