How to Create Data-Driven Resumes to Get Hired for a Prized Job

When you apply for a job it is likely that there are dozens if not hundreds of other candidates who have applied for the same position. You need a resume that is easy to scan for the HR department or AI resume screening algorithm to ensure your skills and achievements are highlighted in a matter of seconds. By using a data driven resume you can leave a positive impression on your potential employer. Learn all about how to create data driven resumes to get hired for a prized job from our detailed guide below.

What is a Data Driven Resume?

A data driven resume emphasizes on data that supports your competence, achievements and shows how you can fit in a company which has a data driven approach. Data driven resumes are important for jobs which require data collection, automation, analysis, reporting, etc.

When are Data Driven Resumes Relevant?

You can use a data driven resume when your job requirement is associated with data manipulation, analysis, reporting, etc. You can also use such a resume when you are applying for a data driven company or a relevant position, e.g. for a Business Intelligence or Data Scientist related job.

Even if your job is not data driven and the organization you are applying for does not deal with data, you can highlight your key achievements using data. For example, you can be a network support engineer applying for a job in the IT department of an organization. In such a case you can highlight the percentage of efficiency you brought in reducing end user complaints, making the network efficient or other key achievements of this kind. Similarly, a child protection expert applying for a non-profit organization which deals with child protection issues can represent the number of child protection cases he/she has handled over the years. He/she can mention the percentage of the success rate for the satisfactory resolution of such cases.

You can be from virtually any industry to make use of a data driven resume. However, jobs and organizations that deal with data are more likely to be suited for such a resume.

Things to Consider when Making a Data Driven Resume

Here are are a few things to consider when you make a resume. For other considerations, check out our article on how to construct a resume.

1. Is the Data Relevant?

There is no point in making a data driven resume when the data is not relevant. You don’t need to discuss how successful your organization was if you don’t have a measurable and verifiable role that you played in that success. In case you don’t have statistics to back your success, it is better not to use data at all.

Example:

If you claim in your resume that during your time at a company the organization achieved 45% reduction in costs, this does not show your achievement. However, if you were to mention that a cost saving mechanism you introduced helped the organization reduce 10% of their costs, contributing to an annual cost saving initiative that resulted in a 45% overall reduction, this shows that you significantly contributed to the initiative.

2. Is the Data Impressive Enough?

Some things might be seen as not achievements but a part of your job. Some job related achievements are expected in certain jobs and can be hard to verify for a prospective employer.

Example:

You might claim that the network down time in your job as a network administrator was below 2%. While this might appear impressive at a glance but keeping the network up and running is supposed to be your job. Furthermore, verifying such a claim might be hard for an employer, so it might simply be seen as inflating your successes in a resume. On the contrary, if you were given an award by the organization for such an achievement, you can mention it to provide verifiable information. Since you would have some kind of documentary evidence to back it or you can request it from your current or previous employer.

3. Is the Data Interpreted in a Measurable Way?

The data you add in your resume should be measurable. You can convert your simple looking achievements into something more meaningful by using statistical information.

Example:

Achievement mentioned without data:

“Conducted dozens of training sessions between Jan 2018 – Sep 2019 on big data, consisting of over a dozen participants in each session with excellent instructor rating.”

Achievement mentioned with data:

“Conducted 30 training sessions between Jan 2018 – Sep 2019 on big data, consisting of 15-20 participants each. The average instructor rating was 4.6/5 from feedback forms.”

4. Does the Data Comply with Industry Requirements?

Many project managers in development sector projects associated with human development require a compliance around 90% or more. In case goals are overachieved, the donor organization can consider this is a result of inefficiency. This is because the project manager needs to justify this achievement (e.g. due to external factors like a government run campaign which complemented the project).

Example:

If the project in village X in country Y was meant to raise enrollment rates for primary school children from 12% to 70% in five years and the enrollment rate is raised to 85%, the donor might consider the baseline assessment as faulty. Unless, the government ran an enrollment campaign in the area during the course of these five years which helped overachieve the target. Hence, it is essential to ensure that your data does not contradict industry standards.

5. Does the Data Comply with Legal Requirements?

You need to make sure that you don’t mention anything which might contradict any legal requirements. Sometimes, organizations use methods which are against the law to maximize profits. These could also be methods which might not violate a national but international standard or law and might be deemed as regressive.

Example:

If your organization was involved in data mining in an organization which acquired data without the consent, it will not win you any points on your resume. One of the biggest scandals in recent times of this kind has been the Facebook–Cambridge Analytica data scandal, where the former mined Facebook data without user consent.

Example of a Data Driven Resume

Jonathan Wise

789 Mall, Houston, FL, Phone: +1 (000) 12345678

Experience

Senior Data Analyst at XYZ Company                                        December 2019 – Present

Responsibilities:

• Developing and implementing of XYZ’s data collection and analytics framework.
• Provide support for data-driven solutions such as program design, data aggregation and data analysis.
• Perform cohort analysis for data for clients for identifying trends and correlations in data sets
• Generating EDA (Exploratory data analysis) for clients
• Maintained data marts according to client requirements

Accomplishments:

Developed and implemented XYZ’s new data collection and analytics framework.

Outcome:

• The new framework resulted in a 10% reduction in data collection costs, resulting in an annual $0.2M savings.
• Completed research that helped boost region sales by 25% for XYZ’s Southern division

Junior Data Analyst at ABC Company                                         January 2016 – November 2019

Responsibilities:

• Automation of manual processes using data science techniques
• Identify data sources relevant for the client and automate data collection
• Processing of structured and unstructured data
• Identify trends, patterns and perform cohort analysis
• Collaborate with ABC’s product development teams

Accomplishments:

Automated 15 manual processes of data collection for 8 clients over 2 years.

Outcome:

• 25% cost reduction for ABC Company
• 50% faster data collection for clients
• Time for generation of daily client reports reduced from 12 hrs to 6 hrs

Education

XYZ University – Master’s in Applied Data Science

ABC University – Bachelor’s in Data Science & Analytics

Technical Skills

SAS Enterprise Miner, Oracle, Python, Microsoft SQL, Microsoft Office, Minitab, Tableau

Final Words

Data-driven resumes can be a great way to highlight key achievements in the form of quantifiable data, which can be an impressive way of presenting yourself as suitable for a job. By highlighting your key achievements in a quantifiable manner, you can ensure that employers are quick to add you to the shortlisted candidates. Your data driven resume is only the first step in finding a job, since you should be able to explain the mentioned information from your resume during a job interview with clarity and confidence to reinforce your skills in the mind of your prospect employer.