Career Launchpad: Landing an Entry-Level Data Analyst Job

If you have an aptitude for statistics and are looking for an exciting, lucrative career that offers stability, then you should absolutely consider a career in data analytics. Entry-level roles pay commonly around $75,000, and it’s easy to quickly transition into a position that puts you into six figures. 

Data analytics is a promising career—that’s for sure. But the path to becoming a data analyst isn’t as straightforward, or at least, it can seem that way from the outside looking in. 

Looking to launch a career in data analytics? Then you’re in the right place. Below, we’ll give you a 7-step guide to landing an entry-level data analyst role. 

What Does an Entry-Level Data Analyst Do?

Entry-level data analysts find data that’s relevant to a research problem. They then analyze this data to make meaningful conclusions for better business decisions. Entry-level data analysts don’t work alone. They are usually a part of a larger data analytics team of statisticians and other analysts who create reports based on analyzed data.

How To Become an Entry-Level Data Analyst: A 7-Step Guide

Follow these seven steps to launch a data analyst career in 2023:

Invest Time in Learning (and Go Beyond)

Meeting the educational requirements is the first step to becoming an entry-level data analyst, and there are multiple ways to do so.

University Degree

Though university degrees are not strictly necessary anymore, you can get a bachelor’s in statistics or computer science to start your data analyst career path. Any degree you choose will take 2-4 years and be resource intensive. 

Bootcamp

If you want a more time-efficient career path, consider a data analytics bootcamp. They’re shorter than a full-time degree program, and some even come with a money-back job guarantee. Bootcamps teach you the essentials that you’ll need for your first day on the job and take under a year to complete. 

Self-Taught Route

The self-taught route is ideal for those who love developing personal study plans. You can combine YouTube videos, books, blogs, webinars, and many other resources to curate a syllabus that works for you and matches the requirements of your dream job.

Keep Learning

Your education shouldn’t stop once you’ve landed your first job. A data analytics course can help with that.

The following books are also an excellent foray into data visuals and analysis:

• “Storytelling with Data” by Cole Nussbaumer
• “O’Reilly Python for Data Analysis” by Wes McKinney
• “O’Reilly Practical Statistics for Data Scientist” by Peter Bruce

You can also learn handy hacks and tips from these websites and blogs.

• Dunder Data
• Data Visualization Weekly
• Synced Review

The social media space is worth tapping into as well. Follow these data experts on social media:

• Ben Jones, Founder and CEO of Data Literacy, former instructor for data visualization theory at the University of Washington, and ex-director at Tableau
• Hadley Wickham, an expert in programming languages
• Kenneth Cukier, co-host of the popular tech podcast Babbage

Develop the Essential Skills and Become Proficient With Popular Tools

Here are the relevant skills and tools you need to build a flourishing career in data analytics:

Technical Skills

The following are the technical skills you need to know:

• Data modeling using Excel. Knowing your way around spreadsheets will be integral to 80% of your tasks as a data analyst. You can build complicated data models with an intermediate understanding of Excel. 
• Programming with SQL. SQL is integral for data retrieval and management, which may involve heavy calculations using complex data sets. Junior data analysts and SQL developers use SQL in BI tools to create reports and dashboards.
• Data Visualization. You will spend significant time communicating your findings to external stakeholders. Now this doesn’t mean you need to know data visualization tools inside out, although some courses will help. If your simple slide deck can communicate data effectively, that’s sufficient too.
• Programming languages like Python and R. Knowing how to code is not enough. You must know how to leverage the range of libraries these languages have for various kinds of data analyst tasks. Start with one language (whichever feels more intuitive to you) and move on to the other once you have mastered it.
• Statistical Theory. Applied statistics help you interpret data patterns and identify trends. With statistics, you will know how to organize data effectively and fulfill all the steps within the data analysis process. Consider “An Introduction to Statistical Learning” by Gareth James as a starting point to develop your statistics-related analytical skills.

Soft Skills

Other than problem-solving skills and general interpersonal skills, these soft skills will reiterate your technical know-how:

• Business Acumen. More than mastering any data model or tool, your delivery of business value will be your biggest strength. You need to translate data into business outcomes with a deep understanding of business goals and how to fulfill them.
• Data Storytelling. Related to the previous point, you need to know how to contextualize your data within a business narrative. Converting quantitative data into data-driven insights and value-laden tips will show your business acumen.
• Interpersonal communication. You’ll spend much of your time as a data analyst interacting with other data teams, such as data engineers and scientists. With excellent communication skills, you can minimize misunderstandings and complete tasks faster.

Tools

Here are some essential tools you can focus on at first to maximize your learning:

• Tableau or PowerBI for data visualization
• Excel for data wrangling
• Jupyter Notebook for sharing code amongst teams

Practice Makes Perfect

Now that you have all the knowledge requirements sorted, here are some other tasks to check off the pre-job search list:

Work on Open-Source Projects or Develop Your Own

Open-source projects allow you to contribute on your own time meaningfully. You can test your skills and identify any knowledge gaps you need to work on.

Consider Freelance Work

Once you’re confident in your abilities, you can test the waters with one-off freelance projects. The focus should be to find freelance work that matches your skills so that you can implement what you have learned so far. Freelance platforms like Fiverr and Upwork have numerous data analysis freelance jobs you can tap into.

Find a Mentor

A data analyst expert with years of hands-on experience can significantly enhance your learning journey. As you build your network, you may identify someone you organically gel with who has shared valuable tips. If formally asking someone to be your mentor doesn’t feel right, then try asking them out for coffee. 

Build a Portfolio

Your portfolio must stand out among the hundreds of applicants hiring managers are considering. Here’s how to do that:

• Ensure that every project in your portfolio is well-organized and well-documented. 
• Highlight your most exciting analysis by contextualizing the research problem and building a narrative.
• Post your portfolio in data analyst forums to get feedback.

Your Network Is Your Net Worth

Building your network is one of the most valuable practices to implement from the start. To develop your network, leverage LinkedIn connections, online communities, or in-person meetings.

Pursue an Internship

Interning with an organization can be helpful in multiple ways. First, you’ll get a taste of what it feels like to work with active tasks assigned to you by a senior data analyst. You’ll also get to build your network as you interact with people at various levels in the organization. Lastly, all the projects you work on can be potential additions to your portfolio.

Work Toward the Job You Want

Take these steps to land your dream job:

Narrow Down the Industries You’d Like To Work In

Almost all industries require data analysts, so focus on the ones you find appealing and have the requisite skills for. Healthcare, finance, entertainment, and insurance are some popular options.

Research Each Company Where You’re Applying

Go beyond their website. Track down current employees on LinkedIn and ask them questions about the hiring process. If you can find someone in the same role you are vying for, get an idea about their day-to-day tasks. All these actionable insights will help you give beyond-generic responses in your job interviews. Here are some data analyst companies to consider.

Tailor Your Resume to Each Role

Your data analyst resume needs to be crisp (recruiters still love the 1-page rule) and relevant to the job. Pick a resume format that allows you to highlight precisely what the data analyst job descriptions are looking for. Study the job posting and use it as a “checklist” to ensure you have included everything the employer is looking for.

Prepare for Each Interview

Research the most commonly asked data analytics interview questions, and then practice your answers—Reddit and Slack communities are great for this. Remember to talk through your logic and train of thought when attempting a technical question in an interview. 

Consider Related Roles

Data analyst roles are often considered catch-all jobs, and there are plenty of related job titles to explore. Consider business intelligence analyst or engineer roles with transferable skills. You can also look at marketing analyst or product analyst roles. Although not interchangeable, data architect roles are also considered suitable options for those interested in data analysis.

Career Transition to Data Analytics: Where To Start

Here’s how you can transition to a data analytics career:

Related Career Transition

Job roles like marketing analysts, product analysts, machine learning engineers, and business intelligence analysts are related to data analyst roles. You can transition to pure data analyst jobs without experience in data-specific roles. Start by assessing what gaps you need to fulfill. If you have data analysts in your current establishment, consider doing a trial with them or transitioning to their team.

Unrelated Career Transition

Things get tricky if you are coming from an unrelated field, but you can still use your domain expertise to help with the transition. So for example, if you’ve worked in nursing before, consider a data analytics role with a healthcare company. Start with the basics such as Excel, Tableau, and SQL. Once you have a learning path in place, optimize your LinkedIn, build a professional portfolio, and start applying.

Becoming an Entry-Level Data Analyst: Real-Life Examples and Stories To Learn From

Pendo Manjele

Pendo Manjele’s foray into the working world as a software developer eventually led to a deep dive into data. She has a degree in computer science, but the shift to data analysis required more study through online courses on data analysis.

She recommends Springboard’s Free Data Analysis course, among other free resources like GFC, Microsoft Training Center, and FreeCodeCamp.

Ohema Nae

Ohema Nae’s journey began through a nonprofit organization’s program for 18-24-year-olds looking to enter tech. She had a liberal arts background and no coding or data knowledge. Ohema was proactive during her internship journey as she tried to resolve her team members’ issues. The moment she got a chance to jump on a project related to Tableau, she cemented her spot in the organization.

Her recommendation? Be ready to learn on the job more than anywhere else. Don’t worry about a lack of experience. Find managers who want to invest in your growth by assigning you projects slightly out of your comfort zone.

How Much Can You Earn as an Entry-Level Data Analyst?

Entry-level data analyst salaries fall between $54,619 and $84,040 range. The average salary is $67,801. 

Resources To Find Entry-Level Data Analyst Jobs

It’s time to start applying for entry-level data analyst jobs! Here are the three most accessible ways to find data analyst job listings:

Job Boards

Glassdoor and Indeed will be your go-to choices, but there are other general and niche job boards you should look at, too.

General 

CareerBuilder and Idealist are popular platforms that help with job postings and job-related resources. On these websites, you will find full-time, part-time, remote, or contract work opportunities in the data analysis field. Other options include ZipRecruiter, AngelList (for jobs at startups), and WorkplaceDiversity.

Niche

For jobs specific to the data field, you can check out Kaggle, Digital Analytics Association, Icrunchdata, Tech Jobs for Good (Non-profit sector), and DataJobs.

Network

LinkedIn and Reddit are great places to build your network. You can skip lengthy application processes with referrals from fruitful engagement on these platforms, especially LinkedIn. Build a profile on LinkedIn highlighting your expertise and what stage you are at in your journey. Interact with seasoned data analysts and post about your experiences. 

Slack Communities

You can join the following Slack communities to expand your network:

• Datatalks.club is where data analysts discuss career goals and advice, tech events, relevant books, and other resources.
• Locally Optimistic is another great Slack community for professionals in the data field to discuss career challenges and share advice and resources.
• Data Science Salon comprises data scientists, so it can be helpful for those transitioning from (or to) data science roles.

Related Read: How to Land a Data Analyst Job Offer—Tips & Tricks from a Springboard Alum

How To Become an Entry-Level Data Analyst FAQs

Still have doubts about data analyst careers? Here are some commonly asked questions about data analyst jobs:

Since you’re here…
Switching to a career in data analytics is possible, no matter your background. We’ve helped over 10,000 students make it happen. Check out our free data analytics curriculum to gauge your interest, or go all-in with our Data Analytics Bootcamp.