Getting a job as a data analyst can open up a variety of exciting career paths, including data science, management, consulting, or specialization.
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.
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Launch your career in data analytics. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from Meta in 5 months or less. No degree or prior experience required.
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Average time: 5 month(s)
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Skills you'll build:
SQL, Pandas, Generative AI in Data Analytics, Data Analysis, Python Programming, Marketing, Data Management, Data Visualization, Linear Regression, Statistical Analysis, Statistical Hypothesis Testing, Spreadsheet, Tableau Software
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.
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.
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?
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Prepare for a career as a data scientist. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from IBM. No prior experience required.
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Generative AI, Data Science, Model Selection, Data Analysis, Python Programming, Data Visualization, Predictive Modelling, Numpy, Pandas, Dashboards and Charts, dash, Matplotlib, Cloud Databases, Relational Database Management System (RDBMS), SQL, Jupyter notebooks, Machine Learning, Clustering, regression, classification, SciPy and scikit-learn, CRISP-DM, Methodology, Data Mining, Github, Jupyter Notebook, K-Means Clustering, Data Science Methodology, Rstudio, Big Data, Deep Learning, Quering Databases, Data Generation, Career Development, Interviewing Skills, Job Preparation, Resume Building
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.
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Learn in-demand skills like statistical analysis, Python, regression models, and machine learning in less than 6 months.
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Average time: 6 month(s)
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Skills you'll build:
Data Science, Data Analysis, Python Programming, Jupyter Notebook, Machine Learning, Statistical Analysis, Tableau Software, Data Visualization, Predictive Modelling, Kaggle, Exploratory Data Analysis (EDA), Regression Models, Technical Interview Preparation, Executive Summaries, regression modeling, Effective Communication, Project Management, Sharing Insights With Stakeholders, Cross-Functional Team Dynamics, Asking Effective Questions, Effective Written Communication, Coding, Using Comments to Enhance Code Readability, Probability Distribution, Statistical Hypothesis Testing, Stack Overflow, Exploratory Data Analysis
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.
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Launch your career as a business analyst. Build job-ready skills for an in-demand career in business analysis in as little as 3 months. No prior experience required to get started.
4.6
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Beginner level
Average time: 3 month(s)
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Skills you'll build:
Microsoft Excel, Microsoft Visio, Business Analysis, Stakeholder Management, Data Analysis, Preparing Data, Pivot Tables, Formulas and Functions, Data Visualization, Business Process, Power BI, Chatbot, Stakeholder Communication, Business Analysis Concepts, Quantitative and Qualitative Analysis Methods, Problem Identification and Analysis, Process Modeling, Data Modeling, Formulate Business Case, Impact Analysis, Gap Analysis, Capability Assessment, Stakeholder Information Gathering, Risk Management, Quality Management, Agile, Project Planning, SCRUM
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).
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Unlock your AI-powered efficiency and innovation. Accelerate data insights! Copilot supercharges your data science workflow, automating tasks and generating code, so you can focus on the big picture.
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Average time: 1 month(s)
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AI for Data Science, AI integration, AI output evaluation, Data Privacy, Data Science, Ethical AI use, Critical Thinking, Data Analysis, Data Storytelling, Natural Language Processing, Data Visualization, Generative AI, Data Augmentation, Model Evaluation, Anomaly Detection, Data Validation, Data Cleaning, Data Preparation, Synthetic Data
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 February 2025, according to Glassdoor:
Junior analyst: $71,142
Data analyst: $86,076
Senior data analyst: $120,458
Analytics manager: $130,561
Director of analytics: $182,687
Chief data officer (CDO): $209,884
Data scientist: $118,488
Business analyst: $93,842
Financial analyst: $78,668
Operations analyst: $68,037
Marketing analyst: $76,118
Systems analyst: $108,444
Health care analyst: $89,220
Data analytics consultant: $99,932
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.
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 the Data Engineering Professional Certificate from DeepLearning.AI and Amazon Web Services. In this intermediate-level program, you'll build skills in the five stages of the data engineering lifecycle, including generating, ingesting, storing, transforming, and serving data.
professional certificate
Launch your career in data analytics. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from Meta in 5 months or less. No degree or prior experience required.
4.7
(619 ratings)
30,059 already enrolled
Beginner level
Average time: 5 month(s)
Learn at your own pace
Skills you'll build:
SQL, Pandas, Generative AI in Data Analytics, Data Analysis, Python Programming, Marketing, Data Management, Data Visualization, Linear Regression, Statistical Analysis, Statistical Hypothesis Testing, Spreadsheet, Tableau Software
professional certificate
Launch your career as a Power BI analyst. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from Microsoft. No prior experience required.
4.6
(5,804 ratings)
260,210 already enrolled
Beginner level
Average time: 5 month(s)
Learn at your own pace
Skills you'll build:
Generative AI in Power BI, Data Analysis, Microsoft Excel, SQL, power bi, Power Query, Data Visualization, Design Reports, Design Dashboards, Report Building, Dashboard Creation, Data-driven decisions, Preparing Data, formulas and functions, Data Management, Security Alerting, Data transformation, Data Configuration, Data Modeling, DAX
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