7 Entry-Level Data Analyst Jobs in 2024

August 20, 2024 by Promode

Data analysis has become a vital function for all businesses to operate hassle-free. This need alone has given rise to data analyst jobs.

According to the latest report, the global analytic industry will reach $114.9 billion by 2028, which further indicates that many businesses are looking for skilled data analysts to grow their businesses. 

Today, organizations use data-driven insights to make informed business decisions, and thus, they often look for a workforce that possesses skills like strategic planning, optimizing automated processes, and discovering new opportunities. 

Thus, this article will share insights about the key competencies for 7 entry level data analyst jobs. Let’s have a look!

Core Responsibilities Of Entry Level Data Analyst 

Although the primary responsibilities of a beginner in data analysis are converting raw numbers into meaningful information, it is crucial to understand that you can assist businesses in making better decisions by analyzing data. 

The core responsibilities of a data analyst are-

  • Gathering Data: An analysts need to collect data from various databases by conducting surveys, tracking websites, buying datasets, and finding new sources of data. 
  • Cleaning Data: Analysts should remove inconsistencies and fix errors in data like incorrect, incomplete, or duplicate datasets. 
  • Analyzing Data: An analyst needs to use different types of analysis, such as descriptive, diagnostic, predictive, and prescriptive, to answer questions in his/ her research. 
  • Visualizing & Communicating Data: Analysts use visualization to communicate their findings and let enterprises know about the accuracy and relevance of these findings to their business. 
  • Solving Issues & Supporting Decisions: As analysts, it is your core responsibility to use your findings and insights to help organizations make informed decisions.  

Core Competencies Of Entry Level Data Analyst 

Working as a starting point for your career as an entry-level data analyst requires technical abilities and soft skills. If these skills are mastered, you will be ready for the challenges and opportunities of being an entry-level data analyst role.

Technical Competencies - 

  • Advanced knowledge of programming languages like Python R, SQL, and  
  • Statistical concepts in mathematics like Descriptive statistics, inferential statistics, and Hypothesis testing
  • Data visualization tools like Tableau or Power BI
  • Data wrangling and cleaning by transforming data, removing inaccuracies in datasets, and integrating it to different sources. 

Soft Competencies - 

  • Communication skills to make clear technical reports understandable by non-technical persons too and to collaborate with team members. 
  • Problem solving skills to resolve ambiguous problems through critical thinking, analytical reasoning and innovation. 
  • An eye for detail will help you clean data, assure quality of your data, and document your data sources, methodologies, and code. 

How To Break Into The Field Of Entry-Level Data Analyst? 

To become a junior data analyst, you need to have basic knowledge of statistics and elementary probability theory and the skills to solve problems in algebra.

This will help you build a career as a data scientist in the future. Additionally, you should be programming-oriented and know data structures well. This is also helpful in understanding business processes and making decisions based on insights derived from analyzing such data. 

A few certifications, in addition to those mentioned above, can give your resume extra shine and prove your competence. One good choice is the Google Data Analyst Certificate, which provides a comprehensive curriculum. 

The other alternative is Microsoft Certified Data Analyst Associate, which focuses on Microsoft Power BI and Azure Data Fundamentals. You can check for more online or offline certification programs.

Entry-Level Data Analyst Job Search Strategies 

To find an entry level data analyst work, you must think strategically. Networking within the industry and gaining practical experience through internships or volunteer work can significantly boost your chances. 

  • Networking - Use LinkedIn to connect with fellow data analysts, join relevant groups, or engage in discussions. Attend conferences, meet-ups, or webinars where industry professionals gather.
  • Joining Internships—Another essential way of gaining practical experience and building relationships with mentors while still at an early stage is through internships for beginners in data analytics. These internships will also give you a grasp of what goes on in the industry.  
  • Participating In Voluntary Work- It is not compulsory for you to work as a full-time data analyst. In the beginning, you can choose to do voluntary work or freelance. You can join non-profit organizations or contribute to open-source projects. 
  • Developing Your Skills - Exhaustively learn Excel, SQL, Python, R, Tableau, and Power BI. Moreover, you should develop your communication skills to help you disseminate insights to different audiences.
  • Building A Portfolio- Methodology and insights must be explained clearly in your portfolio. Pick out projects that demonstrate abilities and problem-solving skills. Make your resume shine by building a portfolio that employers won’t miss seeing when looking at potential resumes. 

Starting A Career In The Entry Level Data Analyst (500)

Entry-level data scientist or analyst can work in almost every sector of the industry. These sectors range from technology to finance, insurance to healthcare, e-commerce, and advertising to management. Now, let us discuss potential career paths within these industries. 

Data Analyst Intern  

The intern is the beginning of an entry-level data analyst. You can gain hands-on data analysis experience under experienced professionals' guidance. Large firms often have internships for students or fresh graduates. 

Data scientist interns may assist with data cleaning, building basic data visualizations, conducting research, and supporting data-driven projects.

Junior Data Analyst

You will be assigned different tasks based on your abilities and the company’s requirements. Junior analysts are part of a big team where the senior analysts break down big projects into smaller tasks. 

You must complete these small tasks. It is important to be good at solving problems, as you might be assigned to figure out data issues. Being good at presentations is an added advantage.

Entry Level Operation Analyst

Based on your industry, you have to figure out ways to make things faster or cheaper. For example, if you work at a restaurant, you might study how to reduce customer wait times. In a hospital, you could find ways to improve patient flow.

Here, you must be good with numbers and understand how businesses work. Your job is to use data to find problems and suggest solutions.

Quantitative Analyst

You will work with many numbers to find patterns to help businesses make more money. Many of these jobs are in finance, where you'll use maths to determine how to invest money wisely, manage risks, and find scams.

You need to be good at maths and statistics. Knowing how to use special computer programs like SAS or R is also helpful.

Health Care Analyst

People who work with healthcare data have different kinds of jobs. Some analysts help in healthcare research, others figure out how to make hospitals run smoother, and some work to ensure that healthcare data is safe and useful for everyone.

These jobs need data analysts who are skilled at working with large amounts of information. You should also understand visual data and how to use it to find patterns.

Financial Analyst

A financial analyst works in banks, insurance, venture capital, or funding companies. You have to work with numbers and should be good at analyzing quantitative data. 

At this entry-level financial data analyst post, you have to assess financial performance and provide financial forecasting. Apart from maths, many people use Python to work with financial data, so it is helpful to learn this computer language, too.

Business Data Analyst

A business data analyst must analyze sales, marketing, customer behavior, and operations data. You have to dig through information to find patterns and trends.  

This means gathering data from different sources, organizing it, and figuring out what it means. You also have to develop key performance indicators (KPIs) and provide insights to improve business performance.

Common Challenges For Level Data Analysts 

Entry-level analysts often need help communicating complex technical findings to non-technical stakeholders. You need to bridge the gap between technicalities and nuanced storytelling. 

To remain competitive, it is essential to stay updated with rapidly evolving data technologies and industry trends. Aspiring candidates should overcome technical limitations through continuous learning and seeking guidance from experienced professionals.

Conclusion 

You are now well equipped with the comprehensive knowledge of an entry-level data analyst. Study the challenges, the skills, and the job requirements to prepare yourself for the job. 

Online certifications shall make you job-ready by giving you knowledge of the trending industry. Companies have to make decisions based on data-driven strategies. Hence, the entry level data analyst jobs will boom in the forthcoming years.