Stand out from the data analyst resume stack
In today's job market, using the "spray and pray" resume approach isn't going to cut it. What should aspiring data analysts do instead?
Hey there! It’s Christine - welcome to my newsletter where I share frameworks to get a job as an early-career data analyst twice a month. These insights are rooted in my experience as a former data director at Vimeo and having interviewed, hired, and trained many analysts since 2015.
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In this newsletter, we’ll cover how to get past the resume wall as an early career data analyst - which I call the MINDS framework:
M: Include quantifiable metrics and keywords for all roles.
I: State a clear and unique intention for moving into data.
N: Craft an analytics-related narrative through high-impact bullets.
D: Use a standout design to catch the eye of recruiters.
S: List your technical skills, show-don’t tell your soft skills.
Read time: 8 minutes
A quick story I see among many aspiring analysts today: after self-studying for months, working on portfolio projects, spending hours crafting a resume, and applying to almost 100 jobs, one of my mentees Pat got crickets.
The problem was his resume didn’t stand out from the stack of the ‘923 other applicants’ who have applied to this job (thx for letting us know, LinkedIn).
It may feel like this resume wall is impenetrable - but having worked in analytics since 2015, strong early-career data analysts are still in demand and hard to come by. If you can surface data-relevant experience that actually gets past ATS and resonates with recruiters, you’ll not only get more interviews, but get them fast. Here’s how.
1: Include quantifiable metrics and keywords even for non-data roles.
Your job in the resume isn’t to show the breadth of your experience over the last 5-10 years, it’s to demonstrate that you understand the job of a data analyst. Since much of the data analyst job is about understanding business metrics, you can do this by including quantitative details about projects and experience:
10% click-through-rate
100K+ transaction records
30% increase in Instagram impressions
10 monthly Excel reports
5 healthcare clients
In Pat’s previous experience working in sales and journalism, he had bullets that looked like this:
To help a data manager understand how his work in sales is relevant to data, he updated this bullet to include a business metric:
Notice that it’s not the value of the metric that matters, but the inclusion of the metric itself that demonstrates you speak the data analyst language.
2: State a clear and unique intention for moving into data.
Especially for early-career data analyst roles, managers tend to look for soft skills, motivation, and an enthusiasm for the role and company - these traits are arguably harder to teach than technical skills.
Instead of feeling disadvantaged if you’re transitioning from another industry, think about how your previous experience has taught you analytics-related soft skills, like:
communicating to various audiences
working with stakeholders
project management
attention to detail
working independently and on a team
managing deadlines
Including these traits in a concise bio can help tie your experience together while clarifying your intention to move to data. Here’s an example from a current student, Rui, who’s worked in patent law and research and got 2 interview bites after just 2 weeks of applying:
And another example from another student, Mo, who had worked in education for 10 years and landed a job as a data analyst in London:
These profiles not only have a clear intention for transitioning into data analytics, but tie in how their experience in other industries actually elevates the soft skills that are essential to the role.
3: Craft a narrative around your experience through high-impact bullets.
The biggest downfall I see in early-career or career-transitioner resumes today is one-line bullets that are either generic or completely unrelated to data - I’m talkin’ about lines like these:
Portfolio project example: Analyzed dataset in Excel and SQL to understand trends on housing prices for last 5 years.
Data-related role: Managed bookkeeping records for financial company including monthly sales and revenue numbers.
Noooo. This is essentially wasted space. Go one level of detail deeper to explain the “what”, “how”, and “why” of your work in a way that is relevant to analytics work, adding job-relevant keywords (italicized) where possible:
Portfolio project example: Conducted exploratory analysis and cleaning for dataset with 1M rows in Excel to understand trends in international housing prices over last 5 years. Used SQL to summarize trends; discovered regions with highest growth rates in housing prices were in East Asia. Created dashboard in Tableau to further illustrate trends split by seasons, country, currency, and household size.
Past work example: Responsible for updating and maintaining Excel model used to record-keep 20+ monthly inputs for revenue and operating costs. Coordinated with data team and accounting team to validate accuracy of revenue values. Sent monthly summary email to finance and marketing to update teams on company’s financial performance.
As a data manager, I won’t be woo-ed to interview someone because they’ve worked with a Pulitzer Prize-winning journalist - but I would be woo-ed by their ability to consolidate various data sources and synthesize this findings from this data to non-technical people like public officials.
4: Use a standout design to catch the eye of recruiters.
Recruiters spend less than 30 seconds - if that, honestly - skimming through a resume. An eye-catching format can help you stand out, especially for small to medium-sized companies where recruiters are personally reading through tons of resumes a day.
Here’s a bird’s eye view of the format that my students have used to get interviews - if you’d like a copy, subscribe to this newsletter and it’ll be in your inbox in a few!
5: List your technical skills, show-don’t-tell your soft skills.
Do list technical skills like SQL, Tableau, Excel, Python, Looker, GitHub, DBT in a “skills” section on the resume. But don’t list soft skills here - these need to be backed up through your bullets.
Instead of just listing “project management”, show-don’t-tell your project management skills by going into detail. Imagine you were ad-libbing a sentence like “I showed project management skills when I worked with ____ in order to _____. The ____ I worked on was used by _____ to _____.”
Whenever I see people say they’ve submitted their resume to hundreds of positions and not heard back, it’s a red flag that indicates they’ve used the “spray and pray” approach with an ineffective resume. In today’s market, it’s more efficient to be a standout fit for a fewer number of roles than to be a halfway fit for a large number of roles.
If you’re curious about how things worked out for Pat - he went from sending out almost 100 resumes and hearing very little back, to sending out less than 50 resumes before getting multiple interviews within weeks - including one at Haymarket Media, where he now works as a data analyst doubling his salary from just over a year ago.
In his case, he also used an effective networking technique to expedite his job process - which I’ll chat through in a future newsletter. 😉
I’d love to have your input as I’m building a diverse community of motivated and ambitious data analysts. If you enjoyed this post, consider taking a moment to:
Message me on LinkedIn with topic requests
Check out my YouTube and leave a comment with questions
Refer a friend to get my 1-hour resume workshop recording
Talk soon,
Christine