Table of Contents
Preface
A resume is your first impression and the first step to your dream job. Before you get to talk about your skills, you are judged on the basis of your resume. While there is no perfect resume design, there are a few things that matter when it comes to creating a data analyst resume, specifically. It is hard to gauge what your interviewer is exactly looking for but there are a few do’s and dont’s that will put you on the radar for all the good reasons. This article will be your one-stop guide to creating a data analyst resume that speaks volumes about you, your skills, and also connects you to your prospective interviewer in a good way.
Data Analyst Resume – An Overview
A data analyst is an important addition to any company because only an analyst can derive meaningful insights from huge data chunks. You may be very good at doing this but if your resume isn’t reflecting that, you are already behind in the competition. Talking about competition- it is extremely high. Companies, big and small, want skilled data analysts to drive data-backed business solutions. The craze is evident from the salary range for data analysts in India which is going north with every passing day.
If you are already an accomplished data analyst, then jump on to the steps below. However, if you want to learn it from scratch or brush up on your skills, our courses can be your perfect starting point.
AnalytixLabs is the premier Data Analytics Institute that specializes in training individuals as well as corporates to gain industry-relevant knowledge of Data Science and its related aspects. It is led by a faculty of McKinsey, IIT, IIM, and FMS alumni who have a great level of practical expertise. Being in the education sector for a long enough time and also having a wide client base, AnalytixLabs helps young aspirants greatly to have a career in the field of Data Science.
How to Create Your Data Analyst Resume
A typical and good data analyst resume follows a particular pattern which makes it easier for HR to quickly identify your profile as something worth considering. While creating a resume, you must fill in the shoes of HR and understand from their point of view how difficult their job is. An HR has to go through a ton of resumes, this makes it difficult for them to pay attention to resumes that are cluttered, have an awkward format, are not concise, and have unnecessary information.
Data analyst resume for freshers
Data analyst resume for freshers is particularly challenging as HR has very little information on whether to consider you or not. In addition to this, even if your profile is selected, the head of department or manager or the concerned technical person conducting your interview will again take a look at your resume before starting a conversation with you.
A clear resume can make them know about your knowledge base.
This makes it easier for them to conduct the interview, be on point, and ask questions related to your profile. You, as an interviewee, can raise a red flag if the questions asked are beyond your expertise and knowledge. This not just shows your confidence but also means less awkward silences and feelings of being let down.
Here are a few things that make up a clear and concise data analyst resume. Before that take a look at this sample data analyst resume –
Dissecting data analyst resume structure:
Header/Sections | What to Write |
| Name and Contact Information | The first thing in a resume for a data analyst or for that matter any resume is typically the name of the candidate and their contact information, this includes the contact number, email, and address. In addition to this hyperlinks or URL to your GitHub repository, blog post and LinkedIn is a plus. Make sure this information is at the top of your resume. It should be the first thing an HR sees. Add your name in bold and slightly larger font, followed by contact details in a little smaller font. |
| Summary/Headline | Ideally, you should summarise your resume in 3-4 lines. This should explain your related skill set, experience in the field, technologies you are familiar with, and other accomplishments that can help the reviewer of your profile to quickly consider you for the role. |
| Education/Academic Background | The next is to provide your academic background. This should be in chronological order. This includes the information regarding your school, year of completion, board of certification from 10th grade to 12th, and eventually college. All this information should be accompanied by the percentage or GPA or similar information so that your academic performance can be easily evaluated. |
| Data Analyst related skills | This is one of the most important sections, especially for data analyst resume for entry-level positions. Here you need to provide all the skills that concern an employer looking for a data analyst. More on this is discussed ahead in the article. |
| Work Experience | This is again another highly important section of the resume. Here you need to provide your experience. Ideally, it is better if the experience is related to the field of data analysis. This is another section that is the focal point of the employers. Typically, you should provide the name of the organization you were working with, the duration of employment, designation, and the nature of the job. Additionally, you can describe what exactly you did there or the project that you undertook and the major achievement in 2-3 lines. |
| Hobbies and Other Experience [Optional] | It is always a good idea to not come up as a 1-dimensional being. To give a better impression, you should describe your other skills. These can be soft skills or other skills and more than often can help in judging your candidacy for the job. For example, having experience in school debates can point out that you have good research and communication skills. |
As you can see, the hobbies section is not mentioned in the sample. This is optional. Add this section only of your hobbies that align with your profile as an analyst. Whether you like to sing or cook does not cut the slack for you when it comes to making it to the first round of interviews. But if experimenting with programming languages and creating AI-based app mockups is one of your hobbies, that is a must-add to your profile.
Need a hand in creating your resume? Try using a free template. Our best picks include templates by Novoresume and Canva.
Now that you know what to write, let’s move on to make an analysis of what your employers might be expecting to see in your resume.
Employer’s Expectations on Resume for Data Analyst
As mentioned above, there are certain aspects of your resume that employers pay more attention to. Ace these and your chances of getting selected increase manifold times. A few important aspects can be – experience, achievements, skills, dealing with ATS, etc.
1. Experience
The employer will be interested in knowing if you have ever worked in a job position where your responsibility was similar to that of a data analyst. If you have worked as a data analyst in a previous organization then you must provide details related to it. This can include the description of your project, the type of data you dealt with, and the tools used among other significant aspects. If not directly related, add any experience remotely close to the current profile like a junior analyst or business analyst can also be useful.
What if my experience is unrelated to the profile?
Also, if your previous experience is completely unrelated then you should try to highlight aspects of your previous job that related to the nature of the job of a data analyst. This can include dealing with structured data, creating reports, and graphs, finding patterns, etc. A data analyst resume for freshers where there is no previous past experience, mentions of internships, or independent projects should be there. They should be related to the role of a Data Analyst.
If you are a fresher and this is going to be your first time preparing for an interview, here is a list of questions almost every interviewer asks a newbie data analyst [Bonus: Hints to what you can answer in case you need it] – 40 Top interview questions and answers for a data analyst.
2. Challenges and Achievements
An employer should know what problems you have solved in your past work experience. Highlight projects, challenges, and achievements – however small or big they are. How?
- Mention the main challenge that you faced or the problem statement you were trying to solve
- Talk about how your skills enabled you to overcome those challenges or offer a solution to the problem statement
- Highlight how your solution benefitted the organization
Make sure that your achievement is not generic but quantifiable. For instance, how much money you saved or how much % of the profit you increased for the organization. These things immediately increase the interest of the employer in you. You show real-time results that you can drive making your profile stand out.
This can be a talking point in your interview that can move the interview away from being a generic one and more on something that you will be more in control of.
3. Skillset
As mentioned in the above section, the skill set is something you should mention in the resume and most importantly, it should be related to the field of data analysis. This is extremely important if the data analyst’s resume is for entry-level positions. We will delve into the exact nitty-gritty of this aspect in detail in the next section but on an overall level, you should provide details like
- Tools
- Business acumen
- Reporting skills
- Mathematical and statistical skills, etc.
4. Keyword focussed resume
Once upon a time, an HR would go through resumes manually. Yes, it’s that dated. Today, organizations use software to do the initial filtering. The ATS or Application Tracking System filters out resumes based on rules set by the employer. This makes it easy for the recruitment team to narrow down on profiles that exactly match their requirements. It saves time and energy for the recruitment team.
What does this mean for you?
An ATS works based on rules. These rules include keywords that organizations add to filter out resumes. For instance, if they are hiring for a data analyst, they will have keywords like data analyst, data engineer, data analytics tools, names of various data certifications, and technologies related to data analysis. Having these keywords in your resume, preferably in the headline or summary, increases your chance of passing through the ATS and actually landing up to the recruitment team.
5. Formatting
Lastly, you can use creative formatting schemes as long as they are simple and easy to read. This can include using a straightforward formatting scheme where you provide headings in bold or underline format and use simple bullet points. Make sure that you use a common font such as Calibri, New Times Roman, or something similar to it. If you want to be more creative then you can use templates that use graphics to demonstrate your skillset by rating them, explaining your academic and experience timeline, etc. This can leave a good impression.
Must-Have Skills for Data Analyst Resume
Data analyst skills in a resume need to be laid down and explained as this can make you a potential candidate. There are a number of skills related to the role of the data analyst. Some important skills that are a must in your resume –
Skills | Why you must have it |
| Quantitative Methods | A resume for a data analyst must mention knowledge of dealing with numerical data. This can include techniques to deal with questionnaires, surveys, polls, observations, etc. |
| Data Warehousing | Dealing with relational databases. Having the knowledge of extraction, transformation, and loading (ETL) solutions. Also, the tools used such as Microsoft SQL, etc. |
| Data Mining | You must know how to extract data to identify a pattern in them. The patterns can include anomalies, correlations, and other patterns that can help in understanding what is going on in the organization and even knowing what is going to happen to the organization’s business in the near future. |
| Business Intelligence | Data Mining is of no use if the knowledge cannot be transferred into a business solution. A Data Analyst needs to have a business acumen to use the knowledge gained from data mining and use to find avenues to increase profit, cut costs, minimize risk, etc. |
| Data Structures | Knowing about the different types of data. This can include the various formats where data can exist. Broadly data can be structured, semi-structured, and unstructured. |
| Statistics and Regression | Among the most common skillset data analyst possess is statistics which can help them in identifying relations in the data. Having knowledge of regression can help in identifying future events. |
| Reporting and Visualization | The analysis of a Data Analyst needs to be presented to the leadership in an easily digestible manner that should be devoid of any major jargon. Thus, having good reporting, visualization, and presentation skills is important. Here the tools such as PowerBI or Tableau along with basic skills in creating PowerPoint presentations are required. |
| Communication Skills | Along with providing reports to the leadership, more than often a data analyst needs to verbally communicate their approach, findings, and recommendations. The leadership needs to have an in-depth insight into the methodology undertaken by the analyst. This is where communication skills come in handy. |
| Statistical Computing and Programming Languages | Data analysts are at an advantage if along with statistical and mathematical knowledge they know a few important programming languages. This includes typical statistical computing languages such as SAS, SPSS, and R. However, knowing a conventional programming language such as python can also be highly beneficial. |
| Teamwork Skills | Data Analyst needs to work in a team and having good teamwork skills is important. If you have any previous experience in working in a team then this should be mentioned. |
| Data Models | Data Models take historical data and predict the way forward. They use a regression algorithm but other algorithms that relate to the field of Machine Learning can also be used. Thus, different model-building techniques should be provided if that skill set is available. |
| Data Process Automation | One of the monotonous aspects of the job includes the extraction and preparation of datasets based on which reports are to be created. This data and these reports are often generated on a weekly basis and can be automated. |
FAQs – Frequently Asked Questions
You may have several questions when you start creating your own data analyst resume. However, here are a few questions that can lend you a helping hand in your resume writing.
Q1. How does a data analyst’s resume stand out?
A Data Analyst resume can stand out by concentrating on 3 aspects- Clear format, Skill sets that are related to the profile of the data analyst, and lastly work experience that can demonstrate the implementation of their skillset.
Q2. What skills do you need to be a data analyst?
One should create a data analyst resume sample with at least 10 skills related to Data Analytics. While a number of skills are required to be considered for a data analyst role, there are certain obvious ones. The data analyst skills in a resume include skills that allow you to deal with data such as
- Knowledge of Data Structures
- Types of Data sets
- Data Warehousing
- Database Development, etc
Quantitative skills are required such as
- Statistics
- Regression analysis
- Data models
Tools such as SAS, R, and Python are also required that can help in Statistical Computing, Data Mining, Data Segmentation, Pattern Identification, Data Audit, etc.
Reporting and Business Acumen skills are required to present your insights. Lastly, communication skills are also important to convey your insights to the leadership or clients.
Q3. Engagement: Put down your queries & opinions in the comments below
This article is aimed at providing you with an understanding of how a good Data Analyst resume can be written. If you have any opinions or queries related to this article, then feel free to post and help us in getting more insights.
Conclusion
Jobs for Data Analysts are growing in double digits and to secure a job, having a good resume is of paramount importance. As the demand for Data Analysts increases, so does the competition. To get yourself in the focus of potential employers, one needs to craft a nice resume that can stand your profile out.
A good resume includes a clear format and information related to data analyst-based skills. It must have details on work experience which can invoke the interest of employers in you.
Happy job hunting to you, then.
