Step by Step Guide on How to Find Entry Level Data Analyst Jobs in the USA

Are you looking for Entry level data analyst jobs?

If you like working with numbers and putting things together, you might do well as a data analyst. Data analysts collect, clean, and analyze data to help businesses decide what to do. If you want to work in this high-demand field, here’s how to get started:

  1. Get a good base of knowledge.
  2. Learn more about how things work.
  3. Do projects that use real data.
  4. Make a collection of your best work.
  5. Practice telling people what you’ve found.
  6. Get a job as a data analyst at the entry-level.
  7. Think about getting a certification or a higher degree.

Let’s look at each of these seven steps in more depth.

How do I start working in entry level data analyst jobs

There are jobs in data analytics in many fields, and there is more than one way to get your first job in this in-demand field. Here are some steps to become a data analyst, whether you’re just starting your career or making a change:

1. Get a good base of knowledge.

If you’re new to data analysis, you’ll want to start by developing foundational knowledge in the field. A broad view of data analytics can help you decide if this is the right career for you and give you the skills you need to get a job.

In the past, most entry-level data analyst jobs required a bachelor’s degree. Even though many jobs still need a degree, this is starting to change. With a degree in math, computer science, or a related field, you can learn the basics and improve your resume. However, you can also know what you need through other programs, such as professional certificate programs, boot camps, or self-study courses.

2. Learn more about how things work.

To get a job in data analysis, you usually need specific technical skills. These are some essential skills you’ll probably need to get a job, whether you learn them in a degree program, through a professional certificate, or on your own.

  •  Statistics
  • R or the Python language
  • SQL (Structured Query Language) (Structured Query Language)
  •  Data visualization
  •  Cleaning and preparing the data

 Look at some job postings for positions you’d like to apply for and focus your learning on the specific programming languages or visualization tools listed as requirements.

In addition to these hard skills, hiring managers also look for workplace skills like good communication skills (you may have to present your findings to people who don’t know as much about technology), the ability to solve problems, and knowledge of the industry in which you want to work.

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3. Do projects that use real data.

Working with data in real-world situations is the best way to learn how to find value in it. Look for courses or degree programs with hands-on projects using real data sets. There are also many free public data sets that you can use to do your projects.

Dig into climate data from the National Centers for Environmental Information, delve deeper into the news with data from BuzzFeed, or come up with solutions to looming challenges on Earth and beyond with NASA open data. These are just a few examples of the kinds of data that are available. Find some information about a subject you’re interested in and use it to practice.

Tip: Coursera’s data analysis library is an excellent place to get more ideas. Guided Projects are a set of hands-on, guided activities that you can do in less than two hours.

4. Make a collection of your best work

Make sure to save your best work as you play around with data sets on the Internet or do hands-on assignments in your classes. Hiring managers can see your skills in a portfolio. A good portfolio can help you get a job lot.

 As you start to put together work for your portfolio, pick projects that show you can:

  • Scrape data from different sources
  • Normalize and clean up raw data
  • Use graphs, charts, maps, and other ways to show what you’ve found.
  • Get valuable information from data.

If you’ve done any group projects as part of your learning, you might also want to add one of those. This shows that you can work well with others. If you’re unsure what to put in your portfolio or need ideas for projects, spend some time looking at what others have put in theirs.

Tip: Create an account on GitHub and start sharing your projects and code there. It’s a great place to meet other data analysts, show off your work, and maybe even get the attention of recruiters.

5. Practice telling people what you’ve found

It’s easy to get caught up in the technical parts of data analysis and forget about how to communicate. As a data analyst, presenting your findings to decision-makers and other important people in the company is an essential part of your job. When you can use the data to tell a story, you can help your organization make decisions based on the data.

What does making decisions based on data (DDDM) mean?

Data-driven decision-making, sometimes shortened to DDDM, is the process of making strategic business decisions based on facts, data, and metrics instead of intuition, emotion, or observation.

This might seem obvious, but in practice, not all organizations are as data-driven as they could be. McKinsey Global Institute, a global management consulting firm, says that data-driven companies are better at getting new customers, keeping customers loyal, and making more money than average.

Practice giving talks about what you’ve learned as you finish projects for your portfolio. Think about the message you want to send and the images you’ll use to back it up. Try to speak slowly and look people in the eye. Use the mirror or your classmates to help you get better. Try recording yourself while giving a presentation to look for ways to improve.

6. Get a job as a data analyst at the entry-level

After you’ve worked with data and presented your findings for a while, it’s time to clean up your resume and apply for entry-level jobs as a data analyst. Don’t be afraid to apply for jobs even if you don’t think you’re a perfect fit. Your skills, portfolio, and interest in a role are often more important than whether or not you meet every bullet point on the list of qualifications.

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If you are still in school, ask the career services office at your school if there are any internships you can do. With training, you can start getting real-world experience for your resume and use what you’re learning on the job.

7. Think about getting a certification or a higher degree.

As your career as a data analyst continues, think about how you want to move up and what other skills can help you. Certifications like “Certified Analytics Professional” or “Cloudera Certified Associate Data Analyst” could help you get better jobs that pay more.

To become a data scientist, you might have to get a master’s degree in data science or a related field. Not every job needs a graduate degree, but having one can open up more doors.

How to become a data analyst if you don’t have any experience

You don’t always need a degree to get a job as a data analyst. Employers are looking for good data analysts who want to know that you have the skills to do the job. If you don’t have a degree, put your best work in your portfolio and make it shine.

1. Identify your transferable skills.

It’s easy to forget that you’ve probably built up a solid set of skills throughout your career. Sit down and take stock of the skills you already have. Think about the skills you’ve found and how they could be used in a career in data analytics.

2. Learn how to do things.

Read “The top skills data analysts will need in 2022” to find out what skills you need. Then look for classes that can teach you how to do these things. You can choose to go at your own pace and sign up for free online courses. Consider certificate programs if you want a program with more structure but still a lot of freedom.

3. Consider a certificate program.

To become a data analyst, you don’t need a degree, but you do need to build up your technical skills and basic knowledge. Signing up for a certificate program is the best way to do this quickly. The best programs are based on projects and help students find career resources. Coursera can be used right away. Coursera’s Google Data Analytics Professional Certificate is an excellent way to prepare for a job as a data analyst without spending time or money on a degree.

You don’t need any experience or a degree to learn how to clean and organize data with SQL and R, visualize it with Tableau, and do a case study for your portfolio. After you finish, you’ll be able to apply directly to Google and more than 130 other US employers for entry-level jobs.

Why?

  • A hands-on curriculum helps you learn the skills by giving you the chance to use them.
  • Projects help you build a portfolio that shows potential employers what you’ve done.
  • Programs that help you with your job search and prepare you for it
  • The cost of these programs is less than the cost of going back to college.

If you’re worried about how much the program will cost, look into your company’s education benefits. You might be able to get money from your employer to pay for school, or your employer might pay for it themselves. Check here to see if you qualify.

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4. Use your projects to make a portfolio.

You need a portfolio if you do not have any experience with data analytics. Employers want to know that you can use what you know in the real world. You can put together a portfolio by using projects from your certificate program, working as a freelancer, or giving your data skills to a small business or nonprofit organization for free.

The kinds of projects you should include in your portfolio show you can:

  •  Scrape data from different sources
  • Clean up raw data
  • Show what you’ve found.
  • Get insights that can be used.
  • Set up alerts for entry-level data analyst roles.

Set up alerts on job boards if you want to find opportunities outside your company. People often forget this step, but it makes your life easier! You can do this on Indeed, LinkedIn, Glassdoor, and Way up to get notified when a data analyst job that fits your criteria is posted.

You can also list the companies you want to work for and schedule time on your calendar to check their job boards. Set up an informational interview by getting in touch with people who work at the companies you want to work for. Don’t forget that networking is how most jobs are filled, so don’t be afraid to put yourself out there.

5. Focus on the industries that are hiring the most people.

If you don’t have a strong desire to work in a specific industry but still want to learn more about which industries are hiring data analysts, check out this list of the top 3 companies hiring data analysts in each of the five industries listed.

6. Update your resume.

Once you’re sure a job posting is what you’re looking for, make changes to your resume to highlight experience that fits the job’s needs. Make sure to proofread and ask someone to look over your resume.

7. Get ready for your first interview to become a data analyst.

You did a great job setting up interviews. This last tip will set you up for success and help you get ready to ace the interview. Most companies will have a phone interview with a recruiter or hiring manager that lasts 30 to 40 minutes. This interview gives them a better idea of who you are and if you might be a good fit for the job. We put together a few blog posts to help you stand out during your interview for an entry-level data analyst job.

Are you prepared to begin your new job?

 Whether you want to be a data analyst in Nigeria or in the USA want to switch jobs or move up in your current company. The Data Analytics Certificate Program is made to help you learn more about data analysis and how to use the right tools for a data job. 

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