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Entry Level Data Analyst Resume No Experience

Are you a recent graduate or someone looking to transition into a data analyst role but lacking professional experience?

Crafting an entry-level data analyst resume with no experience can be challenging, but it’s not impossible.

In this post, we’ll provide you with a sample resume and a step-by-step guide on how to create a compelling resume that highlights your skills, education, and potential.

Whether you have completed coursework, personal projects, or internships, we’ll help you showcase your abilities and increase your chances of landing that first data analyst position. Let’s dive in!

Sample Resume for Data Analyst With No Experience

Peter Davis (000) 142-7147 [email protected] New York, NY

OBJECTIVE Dedicated and detail-oriented individual with a strong analytical mindset, seeking an entry-level position as a Data Analyst. Bringing a solid foundation in data analysis techniques and tools, including proficiency in SQL and Excel. Eager to apply my skills and contribute to the success of a dynamic team in a data-driven environment.

EDUCATION Bachelor of Business Administration State University, New York, NY – 2023

Data Analysis of Sales Trends Analyzed sales data to identify trends and provide insights for optimizing sales strategies. Utilized Excel to perform data cleaning, aggregation, and visualization.

Customer Segmentation Analysis Conducted segmentation analysis using SQL to categorize customers based on behavior and demographics, providing recommendations for targeted marketing campaigns.

CORE SKILLS

• Data analysis and visualization
• SQL and database management
• Excel and data manipulation
• Statistical analysis

INTERNSHIP EXPERIENCE

Data Analyst Intern ABC Company, New York, NY Dec 2023 – May 2024

• Assisted in analyzing and interpreting data to identify opportunities for process improvement.
• Conducted data cleaning and validation for accurate analysis.
• Created data visualizations to present findings to stakeholders.
• Completed a number of monthly reports.
• Performed study on forecasts, demand, income, capital, and expense.

Volunteer XYZ Company, New York, NY Jun 2023 – Dec 2023

• Prepared income and demand presentations in PowerPoint and Excel.
• Performed marketplace analysis to attain product goals and strategies.
• Lead the planning, recognition, development, and completion of design and changes to keep product metrics reports.

CERTIFICATIONS Introduction to SQL Online Learning Platform, 2023

Data Analysis with Excel Certification ABC Online Course Provider, 2022

ADDITIONAL CAPABILITIES

• Problem-solving and critical thinking
• Strong attention to detail
• Effective communication skills
• Team collaboration

Strong references available

How to Write an Entry-Level Data Analyst Resume with No Experience?

Writing an entry-level data analyst resume without any prior experience can be challenging, but it’s not impossible. Here are a few tips to help you create a compelling resume:

1. Objective or Summary Statement: Begin your resume with a strong objective or summary statement that highlights your skills, education, and enthusiasm for the data analysis field. Even though you may not have professional experience, emphasize your determination to learn and contribute.

2. Education: Showcase your academic background, including your degree, university name, and graduation date. If you achieved any notable academic accomplishments or participated in relevant coursework, be sure to mention them.

3. Coursework and Projects: Highlight any coursework or projects that demonstrate your analytical skills. For example, if you completed projects involving data analysis, statistics, or programming languages such as Python or R, mention them to showcase your practical knowledge.

4. Skills: List the technical and soft skills that are relevant to the data analysis field. Include skills like data manipulation, statistical analysis, data visualization, problem-solving, and critical thinking. Don’t forget to mention any software or tools you are familiar with, such as Excel, SQL, Tableau, or Power BI.

5. Certifications and Online Courses: If you have pursued any certifications or completed online courses related to data analysis, include them in a separate section. This demonstrates your proactive approach to learning and acquiring relevant skills.

6. Internships or Volunteer Work: If you have participated in internships or volunteered in roles that involved data analysis tasks, include them in your experience section. Even if they are not directly related to data analysis, highlight any transferable skills you gained during those experiences.

7. Projects or Personal Works: If you have worked on personal data analysis projects or contributed to open-source projects, showcase them. This highlights your initiative, passion, and ability to apply your skills outside of traditional work settings.

8. Relevant Extracurricular Activities: Mention any relevant extracurricular activities or memberships in data-related clubs or organizations. This demonstrates your active engagement in the field and your commitment to continuous learning.

9. References: If you have any references available, consider including them. These can be professors, mentors, or supervisors who can vouch for your abilities and work ethic.

Keep your resume concise, well-structured, and visually appealing. Tailor it to each specific job application, focusing on the skills and qualifications mentioned in the job description. With a well-crafted resume, you can showcase your potential and increase your chances of landing an entry-level data analyst position.

Recommended:

• Entry Level Data Analyst Cover Letter Sample
• 20 Entry Level Data Analyst Interview Questions and Answers

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How to Become a Data Analyst With No Experience or Degree

Yes: it’s entirely possible to become a data analyst with no experience or degree—and yes, employers will be open to hiring you.

With the normalization of AI and machine learning , the demand for professionals with an understanding of data analytics is only increasing. Healthcare, retail, and finance industries in particular are leveraging these technologies.

Ready to get your hands dirty? A great way to see if the field is for you is by trying our free 5-day data analytics short course .

In brief, here are the six steps to becoming a data analyst:

1. Complete a project-based data analytics certification 2. Create a data analytics portfolio 3. Identify (and emphasize) your transferable skills 4. Network 5. Continuously learn the latest trends and tech 6. Prepare for job interviews

Now let’s go in more depth on the entire picture:

What does a data analyst do?

Data analysts vs. data scientists, skills required to become a data analyst, is it possible to become a data analyst with no previous experience.

• How to become a data analyst: Step by step guide
• How to increase your chances of getting hired

Industries (and salaries) for data analysts

More of a visual learner? Well, we’ve made a video of the main parts of this article. Take it away, Will!

Ready to jump in? Let’s go.

As a data analyst, it’s your responsibility to turn raw data into meaningful insights. Following the data analysis process, you’ll solve specific problems or answer certain questions based on data and the insights it provides.

You’ll then take these insights and share them with key stakeholders and decision makers, who can take action or plan for the future accordingly. At the same time, data analysts may be responsible for overseeing the overall processes for collecting and storing data, as well as setting guidelines for  data quality .

A great way to gauge what a data analyst actually does on a day-to-day basis is to look at the tasks and responsibilities that are typically listed in  data analyst job descriptions . Based on actual job descriptions posted on  indeed.com , here’s what you can expect to do as a data analyst:

• Develop and implement databases and data collection systems
• Work closely with management to identify critical metrics and KPIs, and to prioritize business needs
• Collect data from primary and / or secondary data sources
• Filter and clean data
• Identify, analyze, and interpret trends and patterns in complex data sets
• Visualize and present findings to key stakeholders
• Build and customize reports
• Develop and maintain dashboards
• Create and maintain documentation regarding data models, measures, and infrastructure as they are developed

Learn more here about what a data analyst actually does.

While data analysts and data scientists at companies share a common goal—helping to make business decisions—they go about it in different ways. An analyst seeks answers to questions.

Meanwhile, a data scientist’s job is to ask very detailed, tactical questions to help inform an organization’s overall strategy. While a data analyst may work within a single division or department (and have detailed knowledge of that division) a data scientist needs to understand the processes, systems, and aims of the organization as a whole.

Learn more about the key differences between data science and data analysis here.

The good news: you probably already have a lot of these skills.

These skills vary widely by position and company, but they act as a good starting point to understand what you’ll learn in a data analytics bootcamp or prorgram.

Soft skills

• Communication, collaboration, and presentation skills
• Problem-solving
• Attention to detail
• Analytical mindset
• Affinity for numbers
• Good organizational skills and an ability to meet deadlines
• Some commercial knowledge or business acumen
• Methodical and logical approach

If you want an example of someone who was able to put these transferable skills to use, look no further than CareerFoundry Data Analytics Program grad Nick Logan . A former teacher, Nick was able to leverage the research, communication, organization, and presentation skills which are part and parcel of being an educator in his his career as a business intelligence analyst.

Hard skills and tools

• Proficiency in Microsoft Excel
• Knowledge of programming and querying languages such as  SQL , Oracle, and  Python
• Proficiency in business intelligence and analytics software, such as Tableau, SAS, and RapidMiner
• Mine, analyze, model, and interpret data
• Work with large, complex datasets
• Solid understanding of data profiling and requirement gathering processes and principles
• Expertise in data visualization
• Communicate findings and to make actionable recommendations for the business
• Deploy commercially viable statistical models

We’ll cut to the chase: It’s absolutely possible, even if you’re starting from the beginning and don’t have any industry experience.

How can we be so sure?

There are several factors that make the data job market relatively accessible for newcomers:

• The significant and rapid growth of the data market
• The global data skills gap
• The value of transferable skills within the data analytics field

Let’s take a look at these in more detail.

The job market for data analysts is booming

According to a report by Precedence Research in 2022, the global data analytics market was valued at $41.39 billion USD. That’s more than double what it was worth in 2015.

In their Jobs of Tomorrow Report (2020) , the World Economic Forum highlights seven high-growth emerging professions, with data and artificial intelligence (AI) showing the highest growth rate at 41% per year.

AI is accelerating demand for data analysts

Knowing which AI data analytics tools to use will become a prerequisite for many firms, which levels the playing field for those looking to become a data analyst with no experience. It’s no wonder that courses and bootcamps have started making learning these tools and skills part of their curriculums.

In their 2024 Predictions Report , research group Forester put it best:

So who’s going to make the most of genAI in 2024? Data and analytics pros who invest in the right people, practices, and data strategies.

There is a global shortage for data talent

The data market is growing at a rapid pace, and businesses are desperately trying to keep up.

Data-driven organizations consistently outperform their competitors , so it makes sense that hiring data experts will be an increasing priority across all industries.

At the moment, though, we’re seeing something of a data skills gap . In a study conducted by NTUC LearningHub , 93% of working professionals said that their workforce is not achieving optimal productivity due to a lack of data skills.

Miro Kazakoff, a senior lecturer at MIT Sloan sums up the issue of data literacy nicely:

“Data literacy has always been a requirement in successful organizations. It’s just that data illiteracy is more obvious now—or data illiteracy just causes more damage now than it used to.”

Data analysts rely on a vast array of transferable skills from other industries

Aside from the fact that data analysts are in high demand, the role itself requires a vast array of skills—many of which you’ll bring with you from other work and life experiences.

Some key transferable skills that will help you as a data analyst include:

• Curiosity and an inquisitive nature
• Excellent communication skills (e.g. being good at explaining things)
• Collaboration and teamwork

And, with employers placing increasing importance on soft skills , it’s certainly worth highlighting these in your applications. We’ll show you how to do this in the next section.

Related watching: Video: Is working in data analytics a good career fit for you?

Case study: Chad

CareerFoundry graduate Chad Stacey is a great example of this. He studied History and worked as a tech recruiter until he decided to take the CareerFoundry Data Analytics Program.

Despite having no prior experience in the industry, he got a job as a data analyst for British newspaper The Telegraph ! It’s a fascinating story , and not uncommon these days.

How to become a data analyst: Step-by-step guide

1. complete a project-based data analytics certification.

You don’t need a full-blown degree to become a data analyst, but you do need a structured and formal approach to learning the necessary skills. The best (and most flexible) way to do so is through a project-based course . Some key things to look for when choosing a course are:

• A hands-on, up-to-date, AI-inclusive curriculum that contributes to your portfolio
• Some form of mentorship
• A certificate of completion
• A focus on job preparation and career advice
• A job guarantee

For help finding the right course, take a look at this comparison of the best data analytics certification programs .

Here at CareerFoundry we offer a top-rated data analytics program that includes mentorship, tutoring, career guidance, and a job guarantee. Get a taste of it with our free 6-day data course.

2. Create a data analytics portfolio

Data analytics is a hands-on field, and employers want to see proof that you can apply what you know to real projects.

Here are some ideas:

• Take a course that includes projects in the curriculum
• Work on passion projects. We’ve put together some fun data anallytics portfolio project ideas in this guide
• Volunteer your data skills

Learn more more about how to build a professional data analytics portfolio in this guide .

3. Identify (and emphasize) your transferable skills

If you’re brand new to the field of data, it’s especially important to draw parallels between your previous experience and your new career. Spend some time identifying your core hard and soft skills, and think about how they might be transferred to data analytics.

Perhaps you have a marketing background and are already familiar with some basic analytics tools. Maybe you’re a teacher, which makes you great at explaining things.

As Chris Savage, Founder and CEO of Wistia famously wrote on his blog :

“You can’t run a business today without data. But you also can’t let the numbers drive the car.”

Can you see how seemingly unrelated experience will actually set you apart as an excellent data analyst? The trick is to recognize your value and convey it to employers through your portfolio, your resumé, and how you talk about yourself in interviews.

4. Network 

I’ve found this to be a constantly underrated step when learning how to become a data analyst. Networking is a great way to learn about new job opportunities, get advice from experienced professionals, and build relationships that can help you advance your career.

How to go about doing it? After building a social profile so that people can find and connect with you easily, try and attend industry events or data meetups, connect with people on LinkedIn, and reach out to people you admire in the field for coffee chats or informational interviews.

5. Continuously learn the latest trends and tech

The field of data analytics is constantly evolving, so it’s important to stay up-to-date on the latest trends and technologies. Read industry publications, attend conferences (on- or offline), and take online courses to learn about new tools and techniques.

It’s important to recognize that it’s easy to get overwhelmed and feel left behind . Stop, take a breath, and realize that’s near-impossible to stay on top of absolutely everything.

Finding your niche or passion, and subscribing to the relevant newsletters, blogs, and thought leaders around this area will help you feel in the loop.

7. Prepare for job interviews

Once you start applying for data analyst jobs, be prepared to answer common data analyst interview questions and demonstrate your skills. Practice answering questions about your experience with data analysis techniques, as well as your problem-solving and analytical skills.

Another oft-overlooked thing to concentrate on if you want to become a data analyst is to emphasize your ability to communicate your findings to non-technical audiences . You’ll be working not just within a data team, but with other stakeholders, internal or external. Employers are looking to see not only that you can devise and carry out data analysis, but also that you can explain your results clearly and effectively.

Learn more about how to prepare for entry-level data analyst job interviews here.

How to increase your chances of getting hired as a data analyst

In the absence of industry experience, the best thing you can do to sharpen your competitive edge is to recognize the unique value you bring as a newcomer to the field .

This advice comes from Mike McCulloch, Director of Career Outcomes at CareerFoundry, who specializes in coaching graduates through career change.

Rather than being a setback, having no prior experience in the industry is actually seen as a major asset. As Mike explains:

“Newcomers don’t come with any of the preconceptions that mid-level professionals do. They see the business and its challenges through fresh eyes, and are therefore able to approach it from completely new angles. They don’t yet know what’s possible, so they ask different and unexpected questions. Not only does this keep seniors on their toes; it also helps the business to find new solutions to old problems.”

There are other advantages to hiring complete beginners:

• Mentorship: It gives senior team members the opportunity to mentor someone, which benefits both parties.
• Investing in employee growth: Another benefit that many companies will appreciate is the chance to train someone from scratch and nurture them for future career growth.

When you’re just starting out, you can expect to land the job title of “data analyst” or “junior data analyst.” More specialized roles, such as healthcare data analyst , will require some industry experience.

As a newly qualified analyst, you’re likely to find job opportunities in the following sectors:

• Media and entertainment
• Wellness and fitness
• Transport and logistics

…to name just a few! For a more specific idea of the opportunities available to you as a newly qualified data analyst, it’s worth searching for “data analyst” or “junior analyst” positions in your local area. Browse sites like LinkedIn , Indeed , and Glassdoor for a well-rounded view of the current job market.

Read more in our guide to entry-level data analyst jobs.

Bear in mind that in 2024 the data analyst skillset has split across a wide variety of positions and roles (like “ sustainability analyst ” for example), so it helps to search first for “analyst” in job sites and company job boards.

How much do entry-level data analysts earn?

According to data from Indeed , the average base salary for a junior data analyst in the United States is $73,404 USD . That’s considerably higher than the national average income of $53,490, so it’s not a bad starting point!

How much you can expect to earn in your first data analyst job depends on where you (or the job) are based, and the sector you’re going into.

Learn more about entry-level data analyst salaries in this article .

Key takeaways and next steps

As a newcomer to the industry, you have plenty of value to offer—and not just despite  your lack of experience, but in many ways, because of it .

Ready to get the ball rolling? Here’s a free introductory data analytics short course to ease you in. And, if you’d like to learn more about forging a career in data, check out the following:

• What is the typical data analyst career path?
• Can data analysts work remotely?
• How to land a data analyst internship

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5 Entry-Level Data Analyst Resume Examples [& Templates]

• Entry-Level Data Analyst

Best for candidates with 3+ years of experience

With your job experience and a stunning resume layout, recruiters will be ready to give your application the official stamp of approval.

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Standout Entry-Level Data Analyst Resume

Modern entry-level data analyst resume, elegant entry-level data analyst resume, professional entry-level data analyst resume.

• Skills & Work Experience

You’re looking to break into data analysis and yet, most jobs you see require some analysis experience. What came first, the work experience or the job requiring work experience?

No worries though, there are other ways to showcase that you’d be an excellent entry-level data analyst hire for any company smart enough to hire you.

The five entry-level data analyst resume examples below have worked to help fellow analysts break into the world of data in 2024, and these resume tips are a great place for you to get started on your job search.

Entry-Level Data Analyst Resume

or download as PDF

Why this resume works

• Relevant courses like Linear Algebra and Statistics are a welcome addition, but what’s really going to spice things up is an internship experience. If you have any, highlight how you’ve used mathematical knowledge and programming skills to clean data and indirectly improve metrics like ROI.

Related resume examples

• Senior data analyst
• Data analytics manager
• Revenue reporting data analyst
• SQL data analyst
• Data analyst

What Matters Most: Your Skills & Work Experience

When you’re looking for your first role in data analysis, any experience counts. Whether it’s an internship or a solo project, put it on your resume! Focus on what you did and the tools you used to do it.

Since you don’t yet have much real-world data analysis experience, your skills section will play a big role in determining whether you get an interview. Recruiters want to see your technical skills here. Vague words like “teamwork” don’t tell much.

9 popular entry-level data analyst skills

• Excel/ Google Sheets
• SQL (any flavor)
• Linear Regression
• Experimentation
• A/B Testing
• Data Cleanup
• Data Visualization

When it comes to your technical skills, if you can answer this question, you should include it on your entry-level data analyst resume: Would I be comfortable being asked interview questions about that tool/ topic?

Sample entry-level data analyst work experience bullet points

Now I know what you’re thinking: “I’m looking to break into data, I don’t have much relevant experience.” Yes, you do!

How did you learn the analysis skills you have? What projects did you work on? Talk about those!

When talking about experience (through internships) or your projects, you want to convince a recruiter your analysis can have impact. So, your bullet points should similarly focus on impact.

We’re math people, so here’s the formula:

[ action you took ] + [ context/skills you used ] + [ outcome of action ]

Here’s a few examples for inspiration:

• [ Built a random forest model ] in [ scikit-learn ] that combined disparate sources into one projection that [ outperformed the mean absolute error of the next best projection by 14% ]
• [ Built data visualizations ] using [ SQL and Tableau ] for business KPIs that [ reduced manual reporting work by 10 hours weekly ]
• [ Identified strategic marketing opportunity ] for client [ through detailed analysis with intern team ], making recommendations that [ saved client over $10K in yearly campaign costs ]
• [ Received, cleaned, and prepped data from client ] using [ Python, SQL, and Excel ] to help data scientists build marketing mix models that [ resulted in a lift in ROI of 8 basis points ]

If you’re in a time-crunch or are just looking for a quick reference, this section is for you! We’ve helped thousands of entry-level data analysts land jobs and here are the most common questions and quick-wins to help you.

Top 5 Tips for Your Entry-Level Data Analyst Resume

• That teen summer job you spent serving ice cream? By our estimation, you demonstrated reliability, organization, and collaboration. The point is, when you’re looking for an entry-level role, recruiters don’t expect years of relevant experience.
• Since most applicants for entry-level data analyst roles don’t have much experience, a great way to differentiate yourself is to customize your resume and use a cover letter maker for each company you apply to. More work, yes, but a higher success rate.
• A career summary is just that, a summary. As an entry-level data analyst you likely don’t have an extensive career to summarize. Instead, you may want to add a career objective detailing what you’re looking for in a data analyst role and what you’ll contribute.
• Employers need some evidence that you can go from idea to analysis in a project. This is the value of your projects section as an entry-level data analyst. These can be things you’ve done for class or personally, but you should have something relevant to data!
• When it comes to your technical skills, it’s much better to demonstrate a strong command of a few skills than have a laundry list of skills on your resume. Nothing is a bigger red flag to recruiters then when they see five-plus programming languages for entry-level candidates.

Frequently Asked Questions

• Ideally, you can make your entry-level data resume take up one nice, full page. But, it’s better to have a shorter resume than to add a lot of filler content. Remember, recruiters know you’re applying to an entry-level role, they don’t expect an extensive working background. The goal of your resume is to convince them you can do the job, not that you necessarily have done the job.
• Projects, projects, projects. As an entry-level data analyst projects are the best (and sometimes only) way to demonstrate your competency. These projects can be anything. Just ask a question, think of data you can use to answer that question, and do a short write-up of your analysis (any public forum you can link to for this is good).
• A bit of a leading question, I admit. But yes, of course, include any relevant courses you took in school. For our co-founder, including his game theory class led to some interesting conversations in interviews. Similarly, while they’re not as important later in your career, certifications can demonstrate you have the capacity and willingness to learn data analysis.