PROFILE BUILDING + APPLICATION PACKAGE
You submit your resume.
Somewhere between the application portal and the recruiter, you imagine an AI model reading every bullet and deciding your future.
Maybe.
Maybe not.
But that is not the most useful question.
Whether the first filter is automated, rules-based, recruiter-led, or some combination, your application still has to make its meaning easy to extract.
That is where many master’s resumes lose clarity.
You can optimise for a machine and accidentally weaken the human version
You have probably seen advice to “beat the ATS.”
Add keywords. Repeat the job title. Include every relevant skill. Use consulting phrases.
So you add:
strategy, problem-solving, analytics, leadership, stakeholder management, communication, teamwork, market research, Excel, PowerPoint.
Now your resume contains the words.
It still may not contain the proof.
Keywords can label evidence. They cannot replace it.
“Strong leadership skills” is a claim.
“Led a five-person team to deliver a market-entry recommendation for a client” is evidence.
If you want to understand the broader role automation can play in recruiting, read AI In Consulting Recruiting: Benefits & Challenges.
The real screening problem may happen before anyone evaluates your achievement
Consider this bullet:
“Leveraged advanced econometric methodologies to interrogate multidimensional datasets and derive strategic insights.”
It sounds impressive.
It also makes the reader work.
Now compare:
“Analysed pricing data across 18 markets and identified two segments responsible for 70% of margin growth.”
The second version is easier to parse because the actor, action, scale, and implication are visible.
That helps almost regardless of who or what reads it first.
| What you optimise for | What can go wrong | Better question |
|---|---|---|
| Keywords | Resume becomes stuffed | Where is the evidence? |
| Technical detail | Meaning gets buried | What decision did this support? |
| Fancy language | Action becomes vague | What did you actually do? |
| Formatting tricks | Parsing becomes harder | Is the structure simple? |
The strange part is that writing for clarity often helps both systems and humans.
So should you remove consulting keywords?
No.
That is the next trap.
Relevant terms can help describe your experience accurately.
The issue is how they enter the resume.
If you managed senior stakeholders, say so.
If you built a financial model, say so.
If you conducted market research, say so.
If you did not, adding those words because they “sound consulting” weakens the application.
Use the vocabulary of the work you actually did.
For a sharper list of useful resume language and how action words change a bullet, read Resume Keywords: Consulting Action Words.
Your master’s title may be less informative than you think
“MSc Business Analytics.”
“MSc Management.”
“MEng.”
“MA International Relations.”
Those labels tell the recruiter something.
But not enough.
Two students from the same program can leave with completely different evidence.
One may have led a client-facing project.
Another may have built a complex model.
Another may have run a society.
Another may have launched something outside school.
A strong resume makes those differences obvious quickly.
There is a simpler test than guessing what the algorithm wants
Give your resume to someone for ten seconds.
Then remove it.
Ask them:
What are the three strongest things this person has done?
If they remember your university, degree name, and software skills, but not your impact, the problem probably is not AI.
Your signal is buried.
That is fixable.
Not by writing for a mysterious machine.
By making the evidence so clear that whichever reader comes first has very little work left to do.