CV/Resume tips for Data & Analytics jobs

Building a good resume is one of the first and most important stages in landing your dream job. Given the current climate, it is more important now than ever to finesse your CV to increase your chances, especially when your resume is the recruiter’s/hiring manager’s first impression of you and can have major effects on their decision.

In this article, we highlight important sections and details that will help to perfect resumes for a career in data & analytics, which are often the most in-demand jobs nowadays. We also recommend checking out DATAHEAD’s guide for job seekers during the pandemic. 

Resume criteria

            First, there are four criteria that your resume should meet:

·       Easy (and appealing!) to read

·       Effective demonstration of experience

·       Appropriate style and language

·       Showcase your value add using tangible examples

Recruiters and Hiring Managers often spend just seconds scanning over a resume; therefore, choosing the right layout that is easy for recruiters and hiring managers to read and follow is very important. There are some fundamental ways to do this, such as (1) aligning your headings to the left and dates/locations to the right, (2) consistent use of size, font, and format, (3) bolding the position (or company), (4) less than 2-line bullet point description, (5) using digits (and not words) for numbers, and (6) avoiding all-caps and over-filling your CV.

We also highly recommend highlighting your value added to the role, instead of mere descriptions of the job duties in the ‘Experience’ section, which we will go more in-depth in the following section.

Resume sections

At a minimum, there are four sections to include on your resume:

1. Introductory and contact information

This section should be at the top of your resume and highly visible, including your name, email address (professional sounding), phone number (optional), and LinkedIn. Your professional portfolio (e.g., Github) should also be included as evidence of digital presence.

We also suggest a short personal summary, which is often neglected but can add great value to your resume, or a headline of jobs you want to work in (not your current role).  An example of a data analyst resume summary can be:

“Process-oriented and meticulous Data Analyst with 3 years of experience. Proficient in analyzing and interpreting data to boost business growth and revenue by x%. Possessing strong SQL, Python, R, and C++ acumen and solving challenging problems by applying data analytics to produce business value.”

2. Professional/ Work experience

This is arguably the most important resume section – start by listing your most recent role or professional data analyst experience. Then, use up to 6 bullet points (per job) to describe your duties, responsibilities, and value-added to your accomplishments.

We highly recommend researching the job description of the role you are applying for and tailor the information on your work experiences to fit these descriptions. Some common duties of a data analyst include:

·       Collecting and extracting data using advanced computerized models

·       Acquiring data from primary or secondary data sources and maintaining databases or automated data processes

·       Identify and implement external services or tools to support data validation and cleansing

·       Interpreting data and analyzing results using statistical techniques

·       Identifying patterns and trends in the datasets

·       Developing and implementing data analyses, data collection systems and other strategies that optimize statistical efficiency and quality

·       Translating numbers and facts to inform strategic business decisions

·       Developing statistical reports to draw valid inferences and present them successfully to management using a reporting tool

Make sure to include any other special data analyst skills, responsibilities, and

achievements that you have acquired in previous positions, as well as relevant projects and publications. You should also specify the tools or software being used for each task, emphasizing your technical knowledge and skills. Including your problem-solving skills in this section is also recommended (e.g., ‘Coming up with solutions to costly business problems by reducing 12% of operating costs’). Finally, we encourage using meaningful numbers or quantitative information to back up your experiences and achievements (e.g., ‘reduce operating costs by 12%’ or ‘resulting in a 21% increase in sales’).

3. Education

Do not spend too much time on this section – keep it short and direct. Include key information such as degree (name, length, and outcome), subject, school, and relevant coursework (optional).

4. Relevant skills

Another highly important resume section is where you can present and underline your (technical) skills more in-depth. In fact, if there is not enough space, focus on highlighting your hard skills more than your soft skills (e.g., for a typical data analyst position).

Similar to the ‘Experience’ section, research the job description of the role you are applying for to extract information on important and relevant skills to include on your resume. For a data analyst, some commonly requested hard skills are:

·       Statistical analysis and predictive modeling techniques (i.e., Statistics & Mathematics)

·       Data mining, data QA, data warehousing

·       Database design and management

·       Programming languages (e.g., HTML5, C++, Java)

·       Problem-solving and troubleshooting

·       Pattern and trend identification

·       Experimental design and survey creation

·       IBM SPSS, Advanced Microsoft Excel, Pivot Tables, Tableau, SAS, SQL

You can also include a visual rating of these skills (instead of simply listing them out) to make your CV easier to notice and more appealing.       

Last but not least, our other advice, in general, is to (1) really pay attention to the job requirements to tailor your information and strengthen your CV, (2) underline your value added to the role as much as possible, (3) always proofread and get a few sets of eyes for minimum errors and a cleaner CV, and (4) do not be afraid to add some (appropriate!) finishing touches to show your individuality.

For more resume and other career tips, get in touch with us to hear from a DATAHEAD specialist consultant! We’d love to help you write an exceptional CV and land your dream job in Data & Analytics.

Pam, Market Research Associate at DATAHEAD