{"id":3796,"date":"2020-09-28T09:00:00","date_gmt":"2020-09-28T07:00:00","guid":{"rendered":"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/uncategorized\/data-analyst-resume\/"},"modified":"2021-09-20T12:03:19","modified_gmt":"2021-09-20T10:03:19","slug":"data-analyst-resume","status":"publish","type":"post","link":"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/data-analyst-resume\/","title":{"rendered":"How to Write a Great Data Analyst Resum\u00e9 (With Examples)"},"content":{"rendered":"<p id=\"what-makes-for-a-great-data-analytics-resum-is-there-a-specific-layout-to-follow-and-what-skills-should-you-highlight-keep-reading-to-find-out\"><strong>What makes for a great data analytics resum\u00e9? Is there a specific layout to follow, and what skills should you highlight? Keep reading to find out.<\/strong><\/p>\n<p>Looking for a job as a data analyst? Exciting times! This fast-growing industry offers tonnes of career development opportunities\u2014and it can pay pretty well, too. Of course, with all this and more going for it, the competition can be pretty stiff. So, as an aspiring (or job-seeking) data analyst, it\u2019s essential to get your resum\u00e9 right. To improve your chances of a job interview, your resum\u00e9 should stand out while ticking all the requirements outlined in the job description.<\/p>\n<p>Whether you\u2019re new to data analytics or looking for your next challenge, this post covers <strong>everything you need to know to create a winning data analytics resum\u00e9<\/strong>. To make things as easy as possible, we\u2019ll use plenty of examples to illustrate the best approach.<\/p>\n<p>We\u2019ll cover:<\/p>\n<ol>\n<li><a href=\"#what-should-you-include-in-your-data-analyst-resum\u00e9\">What should you include in your data analyst resum\u00e9?<\/a><\/li>\n<li><a href=\"#your-data-analyst-resum\u00e9-name-and-contact-details\">A note on your name and contact details<\/a><\/li>\n<li><a href=\"#how-to-write-a-good-introductory-paragraph-for-your-data-analyst-resum\u00e9\">How to write a good introductory paragraph<\/a><\/li>\n<li><a href=\"#top-hard-skills-and-tools-for-your-data-analytics-resum\u00e9\">Top hard skills and tools for your data analytics resum\u00e9<\/a><\/li>\n<li><a href=\"#main-soft-skills-to-highlight-in-your-data-analytics-resum\u00e9\">Main soft skills to highlight in your data analytics resum\u00e9<\/a><\/li>\n<li><a href=\"#work-experience-and-qualifications\">Work experience and qualifications<\/a><\/li>\n<li><a href=\"#other-achievements-and-activities\">Listing other achievements and activities<\/a><\/li>\n<li><a href=\"#entry-level-data-analyst-vs-senior-data-analyst-resum\u00e9s\">What\u2019s the difference between entry-level data analyst resum\u00e9s and senior data analyst resum\u00e9s?<\/a><\/li>\n<li><a href=\"#your-data-analytics-resum\u00e9-the-final-checklist\">Your final data analytics resum\u00e9 checklist<\/a><\/li>\n<li><a href=\"#summary\">Summary<\/a><\/li>\n<\/ol>\n<p>So: <strong>How do you write a great data analyst resum\u00e9?<\/strong> Let\u2019s take a look.<\/p>\n<h2 id=\"what-should-you-include-in-your-data-analyst-resum\u00e9\">1. What should you include in your data analyst resum\u00e9?<\/h2>\n<p>Data analytics jobs can cover a wide range of industries, from sports to healthcare, marketing, the sciences, and more\u2014you can learn more about <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/data-analyst-career-prospects\/\">where a career in data analytics could take you in this guide<\/a>. Despite this, <strong>data analytics resum\u00e9s all ultimately serve the same purpose: To help hiring managers select who to invite for an interview<\/strong>.<\/p>\n<p>A common statistic is that recruiters <a href=\"https:\/\/www.theladders.com\/static\/images\/basicSite\/pdfs\/TheLadders-EyeTracking-StudyC2.pdf\" rel=\"noopener\">only spend 7 seconds looking at each resum\u00e9<\/a>. Whether or not this estimate is accurate, one thing\u2019s for sure: Recruiters are busy people. So make their job easier by <strong>following a standard resum\u00e9 format<\/strong>.<\/p>\n<p>Data analytics resum\u00e9s (like any other) should be <strong>no more than one page<\/strong>. If yours is longer, you should aim to cut it down (there are exceptions, but we cover these in section eight). In general, though, you should include the following on your data analytics resum\u00e9:<\/p>\n<ul>\n<li>Name and contact details<\/li>\n<li>Introductory paragraph<\/li>\n<li>Tools, languages, and skills (this includes hard and soft skills)<\/li>\n<li>Work experience and qualifications<\/li>\n<li>Additional achievements and activities (optional)<\/li>\n<\/ul>\n<p>In the following sections, we explore these in more detail, with examples.<\/p>\n<h3 id=\"should-you-include-a-photograph-and-your-date-of-birth-on-your-resum\">Should you include a photograph and your date of birth on your resum\u00e9?<\/h3>\n<p>You want to stand out, right? What better way to do so than with a nice photograph of yourself? Wrong! If you\u2019re tempted to include a headshot, check the local employment laws for your country or region first. Providing photos (and in some cases dates of birth) can breach equality guidelines. This means that including a picture may automatically disqualify you. This varies on a regional basis, though, so be sure to check before you hit send. However, if in doubt, don\u2019t. With that covered, let\u2019s get going\u2026<\/p>\n<h2 id=\"your-data-analyst-resum\u00e9-name-and-contact-details\">2. Your data analyst resum\u00e9: Name and contact details<\/h2>\n<p>It might sound obvious, but when it comes to your name and contact details, keep things punchy. When you have a one page resum\u00e9, every line counts. Data analysts need to demonstrate excellent visual and communication skills, too, and this should be clear from the very start.<\/p>\n<p>The only contact details you need to include on your resum\u00e9 are <strong>your name<\/strong>, <strong>email address<\/strong>, and <strong>phone number<\/strong>. Avoid nicknames and don\u2019t use your work email address (or that one you created in high school that you haven\u2019t got round to changing yet!)<\/p>\n<h4 id=\"good-example\">Good example:<\/h4>\n<p><em>Joanna Larkin \u2013 202-555-0126 \u2013 J.Larkin@example.com<\/em><\/p>\n<h4 id=\"bad-examplenbsp\">Bad example:<\/h4>\n<p><em>Jo-Jo Larkin \u2013 202-555-0126 \u2013 JoEatsDonuts@example.com\u00a0<\/em><\/p>\n<p>You can also include your postal address if you like, although this isn\u2019t strictly necessary. If you want to show that you live in the city where the job is located, it can be handy to include it, but use your judgment. It can also be a nice touch to provide links to the following:<\/p>\n<ul>\n<li>Website or portfolio. We show you <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/data-analyst-portfolio\/\">how to build a data analytics portfolio in this guide<\/a>.<\/li>\n<li>LinkedIn profile<\/li>\n<li>GitHub account<\/li>\n<li>Other social media profiles<\/li>\n<\/ul>\n<p>However, <strong>only provide links to relevant projects or information<\/strong>. For instance, don\u2019t bother linking to your GitHub if you haven\u2019t uploaded any projects, as this won\u2019t look great. Likewise, make sure your LinkedIn profile is up to date, including any recent, relevant expertise.<\/p>\n<p>Including social media or your blog can also be a great way to showcase your interest in industry trends. For example, your recent social media activity might demonstrate that you take an active interest in the latest data analytics or machine learning developments. Be aware, even if you don\u2019t list your social media accounts, potential employers might search for them. So do a quick mine sweep for anything you wouldn\u2019t want potential employers to see\u2026 We\u2019re talking political views, embarrassing photos, or silly dancing videos (we\u2019ve all got them!).<\/p>\n<h2 id=\"how-to-write-a-good-introductory-paragraph-for-your-data-analyst-resum\u00e9\">3. How to write a good introductory paragraph for your data analyst resum\u00e9<\/h2>\n<p>Next, and perhaps the most important part of your data analytics resum\u00e9, is your introductory paragraph. As mentioned, hiring managers are busy people, and the introduction is the first (and often only) part of your resum\u00e9 that they\u2019ll read. Think of it as your hook. Get it right and they\u2019ll read on. Get it wrong, and it doesn\u2019t matter how great the rest of your resum\u00e9 is\u2014you\u2019ll end up in the \u201cno\u201d pile.<\/p>\n<p>If you\u2019re an experienced data analyst, you can title this section \u201csummary\u201d (i.e. of your experience). If you\u2019re newly qualified, title it \u201cobjectives\u201d or \u201cgoals\u201d (i.e. where you want to go with your data analytics career). Either way, it should be direct, fact-based, enthusiastic, and tailored to suit the job. While this means your introduction will be different for every data analytics resum\u00e9 you send out, this will make all the difference. Let\u2019s take a look at how each option might read:<\/p>\n<h3 id=\"summary-of-experience-for-more-experienced-data-analysts\">Summary of experience (for more experienced data analysts)<\/h3>\n<h4 id=\"good-example-1\">Good example:<\/h4>\n<p><em>Process-driven data analyst with 2+ years\u2019 experience analyzing business data at InfoCorp. Proven track record of boosting marketing leads, leading to a 20% increase in revenue. Special skills lie in predictive analytics and <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/what-is-data-visualization\/\">data visualization<\/a> using Tableau. Keen to build on these skills in an exciting new role.<\/em><\/p>\n<h4 id=\"bad-example\">Bad example:<\/h4>\n<p><em>Two years working in data analytics. Bored in my current role so looking for new opportunities. I\u2019ve got all the essential skills of a data analyst so let\u2019s talk face to face.<\/em><\/p>\n<p>The first example uses active, positive language while highlighting specific skills and experience, e.g. Tableau. It also includes measurable, numerical achievements (i.e. the 20% increase in revenue). The second example is lackluster, negative, passive sounding, and vague. It\u2019s also a little arrogant\u2014don\u2019t simply tell the employer that you meet their requirements. Explain how, with brief examples.<\/p>\n<h3 id=\"objectives--goals-for-entry-level-data-analysts\">Objectives \/ Goals (for entry-level data analysts)<\/h3>\n<h4 id=\"good-example-2\">Good example:<\/h4>\n<p><em>Graduated from John Collins University with a degree in Business Management. Spent three years leading change projects at KPMG. Fascinated by the impact of data on business operations, I retrained as a data analyst. Hoping to blend my newfound data analysis skills with existing business knowledge to bring unique insights to this role.<\/em><\/p>\n<h4 id=\"bad-example-1\">Bad example:<\/h4>\n<p><em>Graduated with a degree in Business Management and am now looking for a career change, so retrained as a data analyst. Open to any entry-level job that requires data skills.\u00a0<\/em><\/p>\n<p>If you haven\u2019t worked as a data analyst before, the main takeaway here is to be positive and to frame your transferable skills and enthusiasm as key reasons for hiring you. Whether your past career was in an office, working in retail, or anything in between, focus on drawing out your transferable skills.<\/p>\n<p>For entry-level roles, good companies will understand that your skills are limited. They will not necessarily expect you to know how to conduct complicated analyses or create complex machine learning algorithms. Ultimately, the hard skills are something you can learn. A good attitude, meanwhile, is rarer to find.<\/p>\n<h2 id=\"top-hard-skills-and-tools-for-your-data-analytics-resum\u00e9\">4. Top hard skills and tools for your data analytics resum\u00e9<\/h2>\n<p>Hard skills (or learned abilities) are vital for any role. They\u2019re especially important for a technical field like data analytics, where you\u2019ll need certain prerequisite skills to do the job. It\u2019s vital, therefore, to list the right hard skills on your data analytics resum\u00e9. This is not only for human eyes. Many companies use automated applicant tracking systems, which search for the correct keywords and filter out resum\u00e9s that don\u2019t fit the requirements. This makes it doubly important to list the appropriate hard skills on your resum\u00e9.<\/p>\n<p>Within the field of data analytics, hard skills can be broadly divided into two categories. These are software (relevant tools and programs) and learned skills (data-specific knowledge, such as <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/what-is-logistic-regression\/\">how to conduct a regression analysis<\/a>). While you don\u2019t necessarily need to separate these on your resum\u00e9, keep them in mind\u2014this will help you stay focused on the story you\u2019re trying to tell.<\/p>\n<h3 id=\"hard-skills-to-include-on-your-data-analytics-resum\">Hard skills to include on your data analytics resum\u00e9<\/h3>\n<p>Always <strong>start by looking at the job description<\/strong>. This will contain the key hard skills that the hiring company needs. They\u2019re often separated into \u201cessential skills\u201d and \u201cdesirable skills\u201d. Make sure you can tick off all the essential skills on the list and include as many of the desirable ones as possible. Include added extras, if appropriate. For instance, if you have a particular interest in, say, prescriptive analytics, or random forest algorithms, it can\u2019t hurt to mention it\u2014even if it\u2019s not explicitly required by the job description.<\/p>\n<h4 id=\"example-1-data-analytics-hard-skills\">Example 1: Data analytics hard skills<\/h4>\n<p>One way to make good use of limited space is to align your skills to <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/the-data-analysis-process-step-by-step\/\">the overarching steps of the data analysis process<\/a>. The following is an example of common skills you might need for an entry-level position, and how you might list them:<\/p>\n<ul>\n<li><strong><em>Research<\/em><\/strong> <em>\u2013 Data mining, survey creation, focus group management<\/em><\/li>\n<li><strong><em>Data management<\/em><\/strong> <em>\u2013 Database design, SQL, pattern identification, data cleaning (e.g. pandas)<\/em><\/li>\n<li><strong><em>Statistical analysis<\/em><\/strong> <em>\u2013 Exploratory data analysis, prescriptive and predictive analysis<\/em><\/li>\n<li><strong><em>Computer science<\/em><\/strong> <em>\u2013 Advanced MS Excel,<\/em><a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/what-is-python\/\"><em>Python<\/em><\/a><em>, R, machine learning algorithms<\/em><\/li>\n<li><strong><em>Visualization<\/em><\/strong> <em>\u2013 Using tools such as Tableau, Knime, MS Power BI, Matplotlib<\/em><\/li>\n<li><strong><em>Presentation skills<\/em><\/strong> <em>\u2013 MS PowerPoint, Jupyter Notebook, R-Notebook<\/em><\/li>\n<\/ul>\n<h4 id=\"example-2-data-analytics-hard-skills\">Example 2: Data analytics hard skills<\/h4>\n<p>If you\u2019re new to data analytics, you can also use \u2018skill bars\u2019 to highlight your level of expertise. Are you a beginner, intermediary, or expert? If you\u2019re a whizz with visualizations or using Adobe InDesign, you can find a nice graphical way to show this (bonus\u2014this will also show off your visualization skills!) Alternatively, you can simply do so using a word processor:<\/p>\n<ul>\n<li><strong><em>Python<\/em><\/strong><em>: Expert<\/em><\/li>\n<li><strong><em>MS Excel<\/em><\/strong><em>: Expert<\/em><\/li>\n<li><strong><em>Tableau:<\/em><\/strong> <em>Intermediate<\/em><\/li>\n<li><strong><em>JavaScript<\/em><\/strong><em>: Intermediate<\/em><\/li>\n<li><strong><em>R<\/em><\/strong><em>: Beginner<\/em><\/li>\n<\/ul>\n<p>This might seem oversimplified, but it\u2019s very helpful for a hiring manager to see a quick list of your hard skills. However, do mention your key skills in more than one place, if possible. For instance, you can incorporate them into your introduction, or in the work experience section of your resum\u00e9. This will increase the chances of a busy hiring manager spotting your hard data analytics skills, as well as helping your resum\u00e9 get through that all-important applicant tracking system!<\/p>\n<h2><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-9687\" src=\"http:\/\/careerfoundry.inbearbeitung.de\/en\/wp-content\/uploads\/2020\/09\/data-analyst-resume-writing-from-home.jpeg\" alt=\"Person writing their resume from home\" width=\"1200\" height=\"600\" title=\"\" srcset=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-content\/uploads\/2020\/09\/data-analyst-resume-writing-from-home.jpeg 1200w, https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-content\/uploads\/2020\/09\/data-analyst-resume-writing-from-home-300x150.jpeg 300w, https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-content\/uploads\/2020\/09\/data-analyst-resume-writing-from-home-1024x512.jpeg 1024w, https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-content\/uploads\/2020\/09\/data-analyst-resume-writing-from-home-768x384.jpeg 768w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \/><\/h2>\n<h2 id=\"main-soft-skills-to-highlight-in-your-data-analytics-resum\u00e9\">5. Main soft skills to highlight in your data analytics resum\u00e9<\/h2>\n<p>It\u2019s easy to assume that hard skills are the only important thing for data analytics jobs. Indeed, they\u2019re highly valuable. However, <strong>you shouldn\u2019t overlook your soft skills<\/strong>. These include things like openness to feedback, the ability to communicate well with different people, and work ethic. Combining soft and hard skills will go a long way to helping you secure an interview.<\/p>\n<p>Important soft skills for a data analyst resum\u00e9 include:<\/p>\n<ul>\n<li>Communication and public speaking<\/li>\n<li>Strong report writing skills<\/li>\n<li>Storytelling abilities<\/li>\n<li>Business sense<\/li>\n<li>Critical thinking, i.e. the ability to think skeptically<\/li>\n<li>Team working (it\u2019s a classic, but it\u2019s still important.)<\/li>\n<li>Time management<\/li>\n<li>Adaptability and creativity<\/li>\n<li>Risk awareness<\/li>\n<\/ul>\n<p>When you\u2019re pressed for space, it might seem a nuisance to include many of these. Rather than simply listing them (as with hard skills), try weaving them throughout your introductory statement, work experience, or additional achievements section. Use examples where possible. This might sound tricky, but it\u2019s actually a good thing, especially if you\u2019re new to data analytics. That\u2019s because many of these abilities are transferable and you don\u2019t need to be an expert data analyst to have them. You could just as easily have picked them up while studying at university or working at an ice cream parlor.<\/p>\n<h3 id=\"work-experience-and-qualifications\">6. Work experience and qualifications<\/h3>\n<p>After your introduction, list your work experience. This will highlight your skills and interests in action. Always list your work experience in reverse chronological order, putting your most recent job first. List the job title, name of the organization, and dates you worked there. Then include a bulleted list of your key tasks and responsibilities (two or three bullets will usually do, unless it was a senior role). If you\u2019ve only worked as a freelancer, you can title this section \u201cprojects\u201d and pick a few of your most interesting ones.<\/p>\n<p>If you\u2019ve worked in two or three relevant positions within data analytics, don\u2019t feel compelled to include an exhaustive list of your entire work history. Just the most impressive roles will do.<\/p>\n<p>Meanwhile, if you have a limited number of past roles, use other experience to highlight your transferable skills. You could also mention any important <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/data-analytics-portfolio-project-ideas\/\">data portfolio projects<\/a> you\u2019ve worked on. Below, you can see how this might look (and how it definitely shouldn\u2019t!):<\/p>\n<h3 id=\"good-example-3\">Good example:<\/h3>\n<p><strong><em>June 2018\u2014Present<\/em><\/strong><br \/>\n<em>Financial Data Analyst<br \/>\nInfoCorp\u00a0<\/em><\/p>\n<ul>\n<li><em>Helped boost marketing leads by 22%<\/em><\/li>\n<li><em>Created data visualizations using Tableau<\/em><\/li>\n<li><em>Generated monthly reports for senior management using pandas<\/em><\/li>\n<\/ul>\n<p><strong><em>May 2017\u2014June 2018<\/em><\/strong><br \/>\n<em>Retail Manager<br \/>\nLucky Scoop Ice Cream Parlor<\/em><\/p>\n<ul>\n<li><em>Managed a team of five, including quarterly appraisals<\/em><\/li>\n<li><em>Proposed solutions for improving customer satisfaction and reducing expenses<\/em><\/li>\n<\/ul>\n<h3 id=\"bad-example-2\">Bad example:<\/h3>\n<p><em>InfoCorp\u00a0<\/em><\/p>\n<ul>\n<li><em>Analyzed data using data analysis tools<\/em><\/li>\n<li><em>Reported to senior management<\/em><\/li>\n<\/ul>\n<p><em>Lucky Scoop Ice Cream Parlor<\/em><\/p>\n<ul>\n<li><em>Told less senior staff what to do<\/em><\/li>\n<li><em>Gave refunds to complaining customers<\/em><\/li>\n<\/ul>\n<p>Past experience and projects needn\u2019t take up lots of space, but they should include key skills and examples. Consider the position of the hiring manager. What can you tell them about yourself that they don\u2019t already know? What will compel them to pick up the phone and ask you for an interview?<\/p>\n<p>After listing past projects and work experience, you should include your qualifications. Just like your work experience, these should be in reverse chronological order. Make sure you include your degree (if you have one) and relevant data analytics certifications. If you\u2019ve completed a <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/best-data-analytics-certification-programs\/\">data certification program<\/a> or a <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/best-data-analytics-bootcamps\/\">data analytics bootcamp<\/a>, this will certainly impress employers, so be sure to feature it prominently on your resum\u00e9.<\/p>\n<h3 id=\"other-achievements-and-activities\">7. Other achievements and activities<\/h3>\n<p>If you have space, it\u2019s nice to <strong>include a section that highlights your other achievements and activities<\/strong> (i.e. those that lie outside work or academic experience). Especially for entry-level data analytics roles, this is a good way to highlight your suitability. In the past, people used \u201chobbies and interests\u201d sections to highlight extra-curricular activities. This is a bit outdated now, but an achievements section runs with this idea by emphasizing things that showcase your abilities. For instance:<\/p>\n<ul>\n<li><strong>Leadership skills:<\/strong> Perhaps you run or participate in a club in your spare time, e.g. sports groups or events?<\/li>\n<li><strong>Relevant interests<\/strong>: Have you contributed to an industry publication? Do you have a blog where you publish on relevant topics, e.g. machine learning or artificial intelligence?<\/li>\n<li><strong>Domain expertise:<\/strong> If you\u2019re applying for a job as a sports analyst (for instance) why not mention that marathon you ran last year? Did you wear a Fitbit? What insights did you obtain?<\/li>\n<li><strong>Awards<\/strong>: Have you won any awards for your work? This could be as simple as \u201cemployee of the month\u201d, a business award, or maybe even a\u00a0<a href=\"https:\/\/www.kaggle.com\/competitions\" rel=\"noopener\">Kaggle challenge<\/a>?<\/li>\n<\/ul>\n<p>If you\u2019re including an achievements section, be clever with it. Only list your hobbies if they\u2019re relevant. For example, \u201cgoing out with friends\u201d won\u2019t tell an employer anything very useful about you, whereas being a regular attendee of a data analytics meetup will. Stay on topic and make sure the items you include sell the best of you. Don\u2019t worry if your data analytics resum\u00e9 doesn\u2019t include everything. Highlight the most compelling things and you can save the rest for the interview.<\/p>\n<h2 id=\"entry-level-data-analyst-vs-senior-data-analyst-resum\u00e9s\">8. Entry-level data analyst vs. senior data analyst resum\u00e9s<\/h2>\n<p>Regardless of the job you\u2019re applying for, the overall layout of your resum\u00e9 should follow the outline we\u2019ve described above. However, if you\u2019re applying for a senior data analyst role, there are a few differences and additions to be aware of.<\/p>\n<h3 id=\"summary--introductory-paragraph\">Summary \/ Introductory paragraph<\/h3>\n<p>Senior data analyst resum\u00e9s won\u2019t get away with any vague wording in the introductory paragraph. Instead, offer a clear idea of your leadership skills, using very specific examples. For instance, you might mention teams you\u2019ve managed, the projects you\u2019ve overseen, and their ultimate outcomes. Always use measurable figures or percentages where possible, such as improved customer retention figures or other key performance indicators (KPIs).<\/p>\n<h3 id=\"qualifications\">Qualifications<\/h3>\n<p>While work experience usually comes before qualifications on any resum\u00e9, if you\u2019ve spent the past seven years doing a Ph.D. in mathematical computing (for example) it might be more relevant to put this first. Meanwhile, if you have any other qualifications or letters after your name, include these at the top, or use a designated heading to showcase them.<\/p>\n<h3 id=\"hard-skills\">Hard skills<\/h3>\n<p>It might seem obvious, but as a senior analyst, your skills section should be more nuanced to reflect the more demanding requirements of a higher-level role. If you\u2019re applying for a more senior data science position (rather than something entry-level) the hiring manager will want to see information about your specific domain expertise. This might include things like engineering, finance, psychological profiling, or other STEM subjects. It should also mention your advanced skills in areas like artificial intelligence, natural language processing, data infrastructures, or algorithms you\u2019ve created.<\/p>\n<h3 id=\"affiliations-groups-and-publications\">Affiliations, groups, and publications<\/h3>\n<p>Senior data analyst resum\u00e9s also need a section that lists volunteer positions, board memberships, or professional affiliations (such as memberships of industry bodies like the <a href=\"https:\/\/www.digitalanalyticsassociation.org\/\" rel=\"noopener\">Digital Analytics Association<\/a>, or the <a href=\"https:\/\/theodi.org\/\" rel=\"noopener\">Open Data Institute<\/a>). You should also list any research papers or other publications you might have worked on.<\/p>\n<h3 id=\"overall-length\">Overall length<\/h3>\n<p>For all the reasons above, senior data analyst resum\u00e9s can break the one-page rule. This is because you\u2019ll need more space to highlight your additional relevant expertise. If possible though, still <strong>aim to keep your resum\u00e9 to two sides<\/strong>. You can always direct employers to your website for more information.<\/p>\n<h2 id=\"your-data-analytics-resum\u00e9-the-final-checklist\">9. Your data analytics resum\u00e9: The final checklist<\/h2>\n<p>We\u2019ve come this far, so let\u2019s not fall at the last hurdle! Silly mistakes can be the death-knell of any job application. Once you\u2019ve completed your resum\u00e9, use the following checklist to make sure it\u2019s as polished as it can be.<\/p>\n<h3 id=\"have-you-researched-the-company\">Have you researched the company?<\/h3>\n<p>Before submitting any resum\u00e9, always research the company you\u2019re applying to. For instance, a resum\u00e9 for a sales analyst role is likely to be quite different from that of a healthcare analyst. Make sure you get a sense of the company culture, what they do, and the language they use. Frame your data analytics expertise to match.<\/p>\n<h3 id=\"have-you-included-all-the-relevant-keywords\">Have you included all the relevant keywords?<\/h3>\n<p>We\u2019ve mentioned this before, but it doesn\u2019t hurt to drive the message home\u2014check that you\u2019ve included the relevant keywords, both for the hiring manager and those pesky applicant tracking systems. Not all companies use them, but if you\u2019re applying for a job online, it\u2019s a real possibility. Better to err on the side of caution.<\/p>\n<h3 id=\"have-you-looked-at-your-data-analytics-resum-with-a-fresh-eye\">Have you looked at your data analytics resum\u00e9 with a fresh eye?<\/h3>\n<p>Printing your resum\u00e9\u2014or even just changing the font on-screen\u2014is a great way to spot any missing information, formatting errors (e.g. inconsistent headings or bullet points), and for giving it a general sense check. If you can, sleep on it. You\u2019ll be surprised what you\u2019ll spot with a fresh eye. If possible, get someone else to check it, too. They may catch mistakes you\u2019ve missed or suggest additional skills and experience that you should include.<\/p>\n<h3 id=\"have-you-backed-up-your-achievements\">Have you backed up your achievements?<\/h3>\n<p>When making grand claims, be sure to back them up. If you\u2019ve said that you specialize in machine learning, prove it\u2014include some examples of your work. Quantifying your achievements will impress a potential employer much more than simply telling them that you\u2019re qualified.<\/p>\n<h3 id=\"have-you-spell-checked\">Have you spell checked?<\/h3>\n<p>Often, applications don\u2019t progress simply because someone has used poor spelling or grammar. An eye for detail and clear communication is vital for data analytics jobs, and your application should reflect this. Don\u2019t just rely on the automated spellchecker, either. These don\u2019t always pick up the nuances of language and won\u2019t catch everything. For instance, you definitely don\u2019t want to get the company\u2019s name wrong!<\/p>\n<h3 id=\"does-your-data-analytics-resum-fit-on-one-page\">Does your data analytics resum\u00e9 fit on one page?<\/h3>\n<p>Too long? It\u2019s OK to get a little creative with columns and bullets if that helps you get everything on one page. It\u2019s also fine to write in note form, as long as what you\u2019re writing makes sense. You can always include additional information on your website or portfolio. Remember: You don\u2019t need to tell employers everything, just enough to whet their appetite for more.<\/p>\n<h3 id=\"save-creativity-for-your-portfolio\">Save creativity for your portfolio<\/h3>\n<p>Creativity is great, and it\u2019s a highly sought after skill for data analysts. However, when it comes to your resum\u00e9, don\u2019t go too wild. Aim for clarity on your resum\u00e9. Use a clear, standard 12-point font and save the real creativity for your portfolio. And, if you need some inspiration for your data portfolio, here are <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/data-analytics-portfolio-examples\/\">nine of the best data analytics portfolios on the web right now<\/a>.<\/p>\n<h2 id=\"summary\">10. Summary<\/h2>\n<p>In this post, we\u2019ve covered the key things you need to think about when you\u2019re writing your data analytics resum\u00e9. To recap:<\/p>\n<ul>\n<li><strong>Follow a standard format:<\/strong> At a minimum, include your name, contact details, an introductory paragraph, a list of key hard and soft skills, work experience, and qualifications.<\/li>\n<li><strong>Include additional achievements and activities<\/strong> if you can, but only list things that are relevant to the role.<\/li>\n<li><strong>Don\u2019t rush your introductory paragraph<\/strong>\u2014it may be the only part of your resum\u00e9 that an employer looks at, so it needs to make an impact.<\/li>\n<li><strong>Include essential hard skills:<\/strong> Data analytics jobs require very specific technical expertise, so it\u2019s vital to include everything listed in the job description, from your Python skills to your knowledge of statistical analysis. Big yourself up, but don\u2019t embellish.<\/li>\n<li><strong>Weave both your hard and soft skills throughout each section<\/strong> and try to mention the important ones in several places.<\/li>\n<li><strong>Keep in mind what the hiring manager is looking for<\/strong>. This will help you stay focused and decide which information to include (and what to leave out).<\/li>\n<li><strong>Keep it short:<\/strong> For entry-level jobs, your data analytics resum\u00e9 shouldn\u2019t exceed one page, but for more senior roles, you can stretch to two.<\/li>\n<\/ul>\n<p>If you\u2019re new to data analytics and want to find out more, why not try our <a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/short-courses\/become-a-data-analyst\/\">free, five-day data analytics short course<\/a>? Meanwhile, for more tips and advice on forging a career as a data analyst, check out the following:<\/p>\n<ul>\n<li><a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/what-are-the-key-skills-every-data-analyst-needs\/\">What are the key skills every data analyst needs?<\/a><\/li>\n<li><a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/data-analyst-job-descriptions\/\">Data analytics job descriptions and what they really mean<\/a><\/li>\n<li><a href=\"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/how-to-interview-for-a-data-analyst-role-questions-and-answers\/\">The common data analyst interview questions you can expect to be asked<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Applying for a job as a data analyst? Learn how to write a winning data analytics resum\u00e9 in this guide, complete with examples.<\/p>\n","protected":false},"author":101,"featured_media":534,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_lmt_disableupdate":"yes","_lmt_disable":"","footnotes":""},"categories":[3],"tags":[],"class_list":["post-3796","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-analytics"],"acf":{"homepage_category_featured":false},"modified_by":"Kirstie Sequitin","_links":{"self":[{"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/posts\/3796","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/users\/101"}],"replies":[{"embeddable":true,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/comments?post=3796"}],"version-history":[{"count":0,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/posts\/3796\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/media\/534"}],"wp:attachment":[{"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/media?parent=3796"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/categories?post=3796"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/tags?post=3796"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}