According to the World Economic Forum’s Future of Jobs Report (2018), stated that the job profiles of Data Analysts and Data Scientists are all set to witness an increasing demand through till 2022. While this is an excellent piece of news for aspiring Data Analysts, it is also true that the competition for bagging these top-ranking Data Science job roles is exceptionally high.
You must convince potential employers that you are the best candidate for the job profile of a Data Analyst. You must set yourself apart from the others. The first attempt towards creating this impression is your Data Analyst resume. After all, it is your Data Analyst resume that will highlight your key strengths, qualifications, skills, and work experience that make you a befitting candidate for the post of a Data Analyst.
If you can create a well-designed, detailed, and concise Data Analyst resume – something that Hiring Managers are bound to get hooked to – your chances of getting interview calls increases significantly.
Today, we’re going to walk you through the entire process of building a compelling Data Analyst resume that’ll help you land your dream job!
But, first things first –
Who is a Data Analyst?
A Data Analyst collects, stores, and interprets data to transform it into valuable business insights that can be used to improve business operations and foster data-driven decision making. Since this job role involves parsing through data, analyzing it, and interpreting it, it is primarily analytical.
Once Data Analysts are able to interpret the hidden information from within large datasets, they must be able to communicate that information effectively to all the stakeholders involved – colleagues, business & management teams, clients, company partners, etc.
read more about- Salary, Job Description, and Skills required to become a Big Data Analyst
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Job responsibilities of a Data Analyst :
Before talking about the responsibilities of a Data Analyst, let’s look at Data Analyst resume samples of top IT companies.
IBM –
Oracle-
Here is a comprehensive list of the primary duties of a Data Analyst
- Acquiring data from primary/secondary data sources and maintaining databases.
- Interpreting data and analyzing the results by applying different statistical techniques.
- Developing and implementing data analyses, data collection systems, and creating strategies to optimize statistical efficiency and quality.
- Providing technical expertise in data storage structures, data mining, and data cleansing to team members.
- Collaborate with QA Analysts, Database Developers, and business & management teams to define business needs.
- Provide quality assurance of imported data.
- Identifying patterns and trends in datasets and develop analysis reports for the same.
- Reporting the analysis results to all the relevant stakeholders of a business project.
- Managing and designing the reporting environment, including data sources, metadata, etc.
- Troubleshooting any issues in the database systems and preparing reports for the same.
- Supporting initiatives for data integrity and normalization.
- Incorporating changes and updates to source production systems.
- Training end-users on new dashboards, upgrades, and other changes in the systems.
- Defining data collection and analysis processes for data acquisition from new sources.
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Skills required for the profile of a Data Analyst :
- Experience in data models and reporting packages.
- Experience in Data warehousing and business intelligence platforms.
- Experience in working with SQL databases and database querying languages.
- Strong coding skills in multiple programming languages (Java, Python, R, etc.) and frameworks (XML, ETL, etc.).
- Proficiency in statistical methods and packages.
- Proficiency in data visualization and reporting techniques.
- Proficiency in data mining, cleaning, and munging.
- Well-versed in database design and architecture.
- Ability to analyze large datasets.
- Ability to write comprehensive reports.
- Strong verbal and written communication skills
- Time-management and problem-solving skills.
- An analytical bent of mind.
Having an idea about the frequently asked question to a Data Analyst would help better, the blog on” Top 18 Business Analyst Interview Questions & Answers” would help you understand better.
Data Analyst Resume Building
– If you are wondering how to build an eye-catching resume, here’s how!
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Present your contact information well
Earlier, resumes would include the full address of a candidate. However, times have changed. Adding your address in resumes is optional now. It is enough to put only your phone number, email address, a one-liner location, and maybe your LinkedIn/GitHub profile.
Don’t include your work email ID, though.
Write Good Summary
A summary’s main aim is to highlight your skills, experience, interests, and accomplishments. It is a crucial part of your resume – think of it as your “sales pitch.” Usually, this is the part that Hiring Managers read first and focus on. So, write a summary that not only highlights your key skills and experience, but is also creative, short, and crisp.
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Give a detailed account of your educational qualifications
When writing the education section, make sure that you list the following things:
- Degree type
- Major (the subject of study)
- University and location
- Honors, awards, and other academic achievements.
Begin by mentioning your highest degree and chalk out the education section in a way that correlates with the job description and requirements.
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Highlight your skills
The job of a Data Analyst demands a specific skill set that should be clearly depicted on your resume. The most in-demand skills for a Data Analyst include Mathematical and Statistical skills, analytical skills, technical skills, problem-solving skills, communication skills, creative thinking ability, and attention to detail.
Here’s how you should present your Data Analyst skills resume –
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Highlight your achievements
As a working professional, you must have had some noteworthy achievements so far in your professional life. Include these achievements in your resume. You can also mention any certifications you’ve obtained along with academic projects you’ve worked on (if any).
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Write a cover letter
If you think having a good, detail-oriented Data Analyst resume is enough to impress Hiring Managers, you are wrong. You need to back up your resume with a persuasive cover letter, as well. Hiring Managers value cover letters so much so that nearly 45% of them toss out resumes lacking cover letters.
When writing your cover letter, do some ground research first (don’t be lazy and use the cover letter from your previous job). Tailor-made cover letters created exclusively to fit the job description at hand works best. Also, it’s great if you can address the cover letter directly to the Hiring Manager (this is why research is essential). In your cover letter, include a few traits of the company (you are applying to) that interest you.
Key pointers to keep in mind while creating your Data Analyst resume
While the points mentioned above show the basic structure of how you should design your Data Analyst resume, here are a few things you should consider:
- Keep your resume simple, short, and concise. Realize what message you wish to convey to potential employers and make sure your resume communicates that vision clearly.
- Keep your resume design properly structured, aligned, and balanced.
- Make sure to portray your interests, passion, and drive to upskill.
- Highlight your work experience in reverse-chronological order.
- Do not include every minor detail of all your past jobs – your resume should draw attention only to those aspects of your professional career that are relevant to the job description at hand.
- Keep your resume limited to one page, and if required, two pages max. Nobody likes to read lengthy resumes.
- Always upgrade your resume to include any and every skill/certification/job that you obtained recently.
Well, there you go – all you need to know about building a Data Analyst resume. Now you can go on and start making the resume that’ll help you land the Data Analyst job role you’ve been waiting for!
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Are data analysts and scientists different?
Data analysts and scientists are two very different roles within data engineering. Data analysts focus on the big picture and provide strategic recommendations and direction. They use data to answer questions and solve business problems. Data scientists, on the other hand, specialize in the essential details of data and use it to solve specific problems. Data analysts and scientists are two of the most important roles in business today. They work together to provide insights that help companies make better decisions and improve the way they operate. However, data analysts and scientists have different backgrounds and areas of expertise, making it hard to tell them apart.
What are the key points which must be included in the resume of technology enthusiasts?
Writing about the academic qualification and the field experience through part time jobs or internships is the most important thing to mention in a resume. It also includes demonstrating that you have the analytical and problem-solving skills to identify the skills and experience required to perform a job, and the transferable skills required to get you to the next level in your career. Showing self-developed softwares and applications makes a positive impact on the interviewer.
What to write in a resume apart from academic achievements ?
While writing a successful resume may seem like a straightforward task, there are a number of skills required for a resume that go beyond simply writing about academics. You need to know how to effectively write in a resume format, and how to adjust your resume to the job you are applying for. You need to know how to write about your experience in a compelling manner, and how to incorporate the skills required for the job according to its description. You also need to be aware of the current trends in writing, and you need to be able to adapt to them. This will also help demonstrate that you can think on your feet and adjust a pitch when the situation calls for it.