How to Write a Data Analyst Resume: A Complete Guide

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Data Analyst Job Description:

Key Skills Required for a Job as a Data Analyst

Data Analyst Resume: Keywords:

Entry Level Data Analyst Resume:

Junior Data Analyst Resume:

Data Analyst Resume Examples:

Data Analyst Resume Sample Templates:

Dat,a Analyst Resume: Objective: 

Data Analyst Resume: Summary

Data Analyst Resume

As it is with any resume, the fundamental details of your data analyst resume are your name, contact details, educational qualifications (in reverse chronological order) and work experience (in reverse chronological order). Apart from these details, there is a set of guidelines to keep in mind while building your resume. But first, let us look at what your job as a data analyst would entail. 

Data Analyst Job Description:

In simple terms, a data analyst job description is to use information to help make business decisions – filter, interpret and analyse data with the objective of deriving information that can then be used by the different wings in your company. For example, if you work for an online business, one of your projects may be to understand the analytics of your website and come up with ways to improve those statistics. For this, you may have to use raw data that you get from tools like Google Analytics, then filter that data out with information that you get from your internal IT team, then interpret that data. You may then have to present your findings and conclusions to another team, say, the marketing team, which will use your findings to improve their marketing strategies. 

A data analyst works on one project at a time. Depending on your company, you may not only have to interpret and analyse the data, you might also have to work with the respective wing of the company in using your findings. For example, after you have submitted your findings to the marketing team, you may have to sit with them and discuss new marketing strategies that are based on your research. For this, you need some relevant skills and competencies. 

Key Skills Required for a Job as a Data Analyst

There is a complete list of key skills that a potential employer would look for in a data analyst candidate. These skills are useful in each step of your work as a data analyst. These skills include

Mathematics, Statistics, and Analytical Skills:

The primary requirement for a data analyst is to be able to comprehend purely numerical data. So, it is necessary that you understand numbers and have the mathematical skill that it takes to analyse them. Then, you would have to interpret the data statistically. You would need to understand statistics and probability, use graphical representations to present your data and observe patterns and relationships that could help in predicting what happens next. 

For example, say your company recently decided to build an amphitheatre in your office. Your current project might be to study the effects of this new development. You would need to find out what its positive and negative results are, and what can be done to improve them. For this, you will be presented with raw data, for example, the number of hours of work put in by different employees over the past week, how many hours they spent at the amphitheatre, how many employees used the amphitheatre and how many didn’t, etc. The thing here is that this data cannot be used in its absolute form. These numbers from this week are completely useless all by themselves. They only come of use when you compare them to last week and the week before that, i.e., a time when there was no amphitheatre around. Once you make these comparisons, you would have to make simple conclusions out of the given data, like “the amphitheatre has helped in increasing productivity as evidenced by the following data…”. 

Interpreting the data in such a form requires strong mathematical and statistical abilities.

Computational Software:

Industry standard software like Structured Query Language or SQL and Python are a necessity for a data analyst. Besides making the process much faster, software also helps in maintaining accuracy and avoiding human error in the process of analysing data. The reason for this is that as a data analyst, you would receive enormous amounts of data. You might need to deal with thousands of numbers on a daily basis. Software like SQL help in managing such amounts of data, updating the data and retrieving specific pieces of data easily. If not for such software, you might have to skim through an endless amount of numbers to get to what you really need. 

Creativity and Problem Solving:

A fundamental part of your job would be to use data to solve any given problem. This would necessitate creativity and problem solving. For example, if your current project is to attract more youngsters to your brand or product, you would have to think the way they do – use your creativity in making your product appeal to youngsters. First you would observe how many youngsters are already using the product, then compare their interests and trends with others within that demographic, then use your own creativity in trying to tap a new market. Granted, this looks like the marketing team’s job. But using the numbers to arrive at usable conclusions is something that only you can do. So, a question you might have to ask yourself constantly is, “How can I use these numbers to solve this problem?”

Critical Thinking and Logical Reasoning:

To do this job to the best of your abilities, you would need to be completely objective and logical in your analysis. Every time you are faced with a problem, you would need to zoom out and look at it from different perspectives to arrive at creative solutions. For this, you would need to be critical of your own thought processes and those of the others in your company. You would need to be objective in that you cannot let your own emotions come in the way of the greater good. For example, you may have helped implement a certain marketing strategy during one of your earlier projects. But this time, you might come to realise that that same strategy is deterrent to the company’s progress. In such a case scenario, you would need to put your own sentiment aside and approach the problem objectively. You would need to be rational, reflective and adaptable.

Communication, Presentation and Teamwork: 

In all of the previous examples, there was a need for the data analyst to present their data to a particular wing in the company. Clearly, an integral part of your career as a data analyst is the communication of your findings and analysis to other wings of the company. You would need to explain to them your conclusions and clear any and all questions that they may have. You would also need to sit with them and brainstorm ideas to use your findings and solve a given problem. Such work mandates good teamworking skills. You would need to be open to new ideas, while at the same time, being assertive and confident about your own work. If you don’t gel well with the others in the company, you wouldn’t be able to do your job as effectively. 

Reporting or Writing Skills: 

Having analysed your data, you would need to condense it into a written report that others can understand clearly. Basically, if you receive numbers as your raw material, then your finished product would be a written report, which you will then need to present to other wings. This written report would need to be crisp and concise, while conveying all important information with sufficient evidence. The report will be used not only for an ongoing project, but also as a standard of comparison for upcoming projects. For example, your current project could be to understand the user engagement on your company’s online platform over the previous month. Next month, if your company requires a similar data analysis, you could use the report from the previous project to make relevant comparisons. These reports will also go into the archives of the company, and they are sometimes used for press releases and public relations projects as well. For this, you need to have good reporting and writing skills. 

Data Analyst Resume Keywords:

While reading your resume, a potential employer may simply look for some keywords, instead of reading it entirely. These keywords include some of the skills listed above, but they also include some other important words. Here’s a complete list of keywords for a data analyst resume. 

Typically, these words include:

  • SQL data analysis 
  • Business data analyst 
  • Python 
  • Machine learning 
  • Critical thinking and problem solving 
  • SAS
  • Excel
  • Pivots
  • Predictive analysis 
  • Statistical analysis
  • Programming languages like R
  • Data mining
  • Coding 
  • Visualisation

Entry Level Data Analyst Resume:

As it is with any profession, entry level data analysts take some time to understand their work environment and adapt to it. You may be given less work for the first few months, or you might be carrying out the work of your higher-ups. But, being proactive and eager to learn more will certainly help – your employers and higher-ups will notice this and give you more to do. This is how you climb the ladder.  

While building your entry level data analyst resume, you won’t have any previous experience to show your potential employers. This could seem like something to be concerned about. However, if you list out your skills and make a mention of other certifications and competitions that you may have taken part in, it makes up for the lack of experience. Employers look for fresh minds who can bring something new to the company. So, if you show that you are capable of being that change in the status quo, there is a very good chance that you get hired. 

Junior Data Analyst Resume:

As a junior data analyst, you may not have as big a say as your seniors. However, an eagerness to learn more will make you stand out. Be sure to talk to your seniors, explore new ideas and concepts with them and simply, be more active.

While applying for the job, include your basic personal details, qualifications and work experience. Also be sure to include everything you learnt from your previous employment opportunities. Make a mention of anything that you may have contributed to the companies you worked for previously. This will show that you are proactive.  

Data Analyst Resume Examples:

It is useful to have some references of successful data analyst resumes while building your own. This can help you understand what an employer looks for and how you can stand out. It is all about seeming unique in a pile of other candidates. Your objective is to convince the employer that you are the right person to hire. Here are some samples that could help.

Data Analyst Resume Sample Templates:

Although you know the basic details to include in your resume, it helps to have a fixed template for your resume. This makes the job much faster, and it also makes your CV look clean and professional. The templates available online have specific spaces for your photograph, address, qualifications, hobbies, etc. Some of these templates are even available on your basic writing software like Microsoft Word

Data Analyst Resume: Objective: 

The resume objective statement is a neat, concise paragraph about who you are, what you want to do, your skills and professional goals. It is important to keep this crisp and professional, as it is the first thing that an employer would read on your resume. List out your experience in short, crisp statements – do not mention the company, simply state how much experience you have had in terms of time. 

Data Analyst Resume: Summary

An effective resume summary is quite similar to the objective statement. However, it is a bit longer and more elaborate. If you are an entry-level data analyst, use this space to talk about your skills and competencies. Show that you have passion and a thirst to learn more. Make sure never to seem like you’re underconfident or engaging in flattery. Do not praise your employers, here or anywhere else throughout your resume. 

A resume is the first step in creating an impression. Your employers could remember you by your resume even after you have started to work for them. This means that a resume is not just a tool to find a job, it helps beyond that stage as well. So, it is good to remember just how important your resume is while constructing it.  

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