Writing a resume for a junior-level data analyst role involves highlighting your education, relevant skills, projects, and any experience that showcases your ability to analyse data. Here’s a step-by-step guide to help you create a compelling resume:
1. Contact Information
At the top of your resume, include your:
- Full name
- Phone number
- Email address
- LinkedIn profile (optional)
- Portfolio or personal website (if applicable)
2. Professional Summary
Write a brief summary (2-3 sentences) that highlights your key qualifications and career goals. This should be tailored to the data analyst role you’re applying for.
Example: “Detail-oriented and analytical recent graduate with a degree in Data Science and hands-on experience in data analysis, visualisation, and statistical modelling. Eager to apply my skills in a junior data analyst position to support data-driven decision-making.”
3. Education / Certifications
List your educational background in reverse chronological order. Include:
- Degree(s) obtained
- Name of the institution
- Graduation date (month and year)
- Relevant coursework (optional)
Example: Bachelor of Science in Data Science
XYZ University, City, Country
Graduated: May 2023
Relevant Coursework: Data Mining, Statistical Analysis, Machine Learning, Data Visualisation
Tip: If you have any relevant certifications, list them in a separate section. If you didn’t have a relevant degree in this field, then mention any necessary certifications here.
For example:
- Google Data Analytics Professional Certificate
- Microsoft Certified: Data Analyst Associate
4. Technical Skills
Create a section to highlight your relevant technical skills. This can include software, programming languages, and tools commonly used in data analysis.
Example:
- Programming Languages: Python, R, SQL
- Data Analysis Tools: Excel, Tableau, Power BI
- Databases: MySQL, PostgreSQL
- Statistical Analysis: SPSS, SAS
- Machine Learning: Scikit-learn, TensorFlow
Tip: The skills section on your resume likely only has room for 2-4 bullet points, so be sure to use this space effectively. You might want to prioritise technical skills over professional skills. This is a great chance for you to highlight some of the skills you’ve picked up in these courses, such as:
- Strong analytical skills
- Pattern recognition
- Relational databases and SQL
- Strong data visualisation skills
- Proficiency with spreadsheets, Python, SQL, R, and Tableau
Notice how the skills listed above communicate a well-rounded data analyst’s skill set without being wordy. The skills section summarizes what you’re capable of doing while listing the technology and tools you are proficient in.
Many companies use algorithms to screen and filter resumes for keywords. If your resume does not contain the keywords they are searching for, a human may never even read your resume. Reserving at least one bullet point to list specific programs you are familiar with is a great way to make sure your resume makes it past automated keyword screenings and onto the desk of a recruiter or hiring manager.
5. Projects
Describe any academic, personal, or professional projects that are relevant to data analysis. Focus on your role, the tools and technologies used, and the outcomes.
Example: Sales Data Analysis Project
- Utilized Python and SQL to analyse sales data for a retail company.
- Cleaned and preprocessed data using Pandas and SQL queries.
- Created visualisations using Matplotlib and Tableau to present findings to stakeholders.
- Identified key trends and provided actionable insights that contributed to a 10% increase in sales.
6. Work Experience
Include any work experience that demonstrates your analytical skills, even if it’s not directly related to data analysis. Use bullet points to describe your responsibilities and achievements.
Example: Intern, Data Analytics ABC Corporation, City, Country
June 2022 – August 2022
- Assisted in data cleaning and preprocessing for market research projects.
- Conducted exploratory data analysis using Python and Excel.
- Developed dashboards in Tableau to monitor key performance indicators.
- Collaborated with senior analysts to identify trends and generate reports.
7. Certifications (optional)
If you have any relevant certifications, list them in a separate section.
Example:
- Google Data Analytics Professional Certificate
- Microsoft Certified: Data Analyst Associate
8. Additional Sections (optional)
You can include additional sections such as:
- Awards and Honours
- Professional Memberships
- Languages
- Volunteer Experience
Examples of sample Resume with details
Here are two sample Resume templates. Click the following links and select “Use Template.”
Link to template 1: Template Example 1
Link to template 2: Template Example 2
Examine the resume templates
First, you’ll make some decisions about the structure and layout of your resume. You’ll start by examining the two templates and decide which format you like best. Spend some time browsing the templates, as well as templates, available to you on the web. Take note of the things you like or dislike about the various formats. It’s okay to take some time and be selective here. You’ll be spending a lot of time on this document, so picking a format you’re happy with will help you get off to a strong start.
Make resume format decisions
Before creating your resume, you need to make some design decisions. While you may make some small tweaks and changes to tailor the content of your resume to specific roles you are applying for, the structure and format of the resume likely won’t change. This means it is important to spend time thinking about how you’ll want to structure your resume.
Keep your resume format concise
There’s no best format for a resume. Instead, think about what you want to highlight about yourself to potential employers.
For instance, if you have relevant work experience, then pick a format to highlight that.
If you are transitioning from a different career and don’t yet have relevant work experience, then you may want to pick a format that highlights your technical skills and portfolio projects. Some resume formats include a Summary or Goals section at the top to help candidates add context to their application, while other resume formats avoid these sections completely and save that space for sections such as Skills and Experience.
Whatever format you pick, make sure to follow the one-page rule and keep the completed version on just a single page. If the one-page rule seems limiting, think about the purpose resumes serve in the hiring process overall. Resumes are short documents designed to communicate the most pertinent information about yourself to recruiters and hiring managers at a glance. These are different from longer, multipage Curriculum Vitae (CV) that exhaustively list every relevant thing the candidate has ever done.
If an employer wants a detailed history of your past work experiences and accolades, they might specifically request a CV (curriculum vitae) instead. If they don’t, always assume they prefer a resume. While it is generally considered acceptable for resumes of applicants with extensive work history applying for senior technical roles to have two-page resumes, these are the exception rather than the rule. When applying for a data analyst position, keep it to one page!
Select a format
Once you decide on a template, resist the urge to begin filling it out. The next lessons will focus on best practices for communicating your skills and experience in meaningful, impactful ways. Keep this resume template handy, as you’ll be working on it further.
Formatting Tips:
- Keep your resume to one page, especially if you have limited experience.
- Use a clean, professional layout with consistent formatting.
- Use bullet points for easy readability.
- Proofread carefully to ensure there are no errors.
By focusing on your education, technical skills, relevant projects, and any work experience, you can create a resume that effectively showcases your qualifications for a junior data analyst role.
Bonus Tips:
First of, Technical Skills
OK, so I can not stress this enough that, how important is technical skills are in this kinda role. After all, this is a technical role, right? So, it is very, very important to learn and then highlight those skills in your resume. Here are few technical skills are “The Must” to know and mention:
1. Structured Query Language (SQL): SQL is considered a basic skill that is pivotal to any entry-level data analyst position. SQL helps you communicate with databases, and more specifically, it is designed to help you retrieve information from databases. Every month, thousands of data analyst jobs posted require SQL, and knowing how to use SQL remains one of the most common job functions of a data analyst.
2. Spreadsheets: Although SQL is popular, 62% of companies still prefer to use spreadsheets for their data insights. When getting your first job as a data analyst, the first version of your database might be in spreadsheet form, which is still a powerful tool for reporting or even presenting data sets. So, it is important for you to be familiar with using spreadsheets for your data insights.
3. Data visualisation tools: Data visualisation tools help to simplify complex data and enable the data to be visually understood. After gathering and analyzing data, data analysts are tasked with presenting their findings and making that information simple to grasp. Common tools that are used in data analysis include Tableau, Microstrategy, Data Studio, Looker, Datarama, Microsoft Power BI, and many more. Among these, Tableau is best known for its ease of use, so it is a must-have for beginner data analysts. Also, studies show that data analysis jobs requiring Tableau are expected to grow about 34.9% over the next decade.
4. R or Python programming: Since only less than a third of entry-level data analyst positions require knowledge of Python or R, you don’t need to be proficient in programming languages as an entry-level data analyst. But, R or Python are great additions to have as you become more advanced in your career.
Secondly, Professional Skills
There is more than just data when it comes to being a data analyst—there are plenty of professional skills that can set you apart from other candidates so that potential employers will notice you and know that you have the ability to succeed in this role. Here are some of the most common professional skills you will find in an entry-level data analyst resume.
1. Presentation skills
Although gathering and analysing data is a big part of the job, presenting your findings in a clear and simple way is just as important. You will want to structure your findings in a way that allows your audience to know exactly what conclusions they are supposed to draw.
2. Collaboration
As a data analyst, you will be asked to work with lots of teams and stakeholders—sometimes internal or external—and your ability to share ideas, insights, and criticisms will be crucial. It is important that you and your team—which might consist of engineers and researchers—do your best to get the job done.
3. Communication
Data analysts must communicate effectively to obtain the data that they need. It is also important that you are able to work and clearly communicate with teams and business leaders in a language that they understand.
4. Research
As a data analyst, even if you have all of the data at your disposal, you still need to analyze it and draw crucial insights from it. To analyze the data and draw conclusions, you will need to conduct research to stay in-line with industry trends.
5. Problem-solving skills
Problem-solving is a big part of a data analyst’s job, and you will encounter times when there are errors in databases, code, or even the capturing of data. You will have to adapt and think outside the box to find alternative solutions to these problems.
6. Adaptability
In the ever-changing world of data, you have to be adaptable and flexible. As a data analyst, you will be working across multiple teams with different levels of needs and knowledge, which requires you to adjust to different teams, knowledge levels, and stakeholders.
7. Attention to detail
A single line of incorrect code can throw everything off, so paying attention to detail is critical for a data analyst. When it comes to understanding and reporting findings, it helps if you focus on the details that matter to your audience.
Adding professional skills to your resume
Here are a few ways that you can add professional skills to your resume:
- Analyse your previous work experience and find opportunities to insert a professional skill. For example, if you worked in a restaurant, you could emphasize your communication and adaptability skills that you utilised to effectively function during peak hours.
- Call attention to your problem-solving, presentation, research, and communication skills in previous projects or relevant coursework.
- Add a mix of professional and technical skills in the skills or summary section of your resume.
