Hi, I’m Ayo

I fix broken workflows, including my own, with

I ship products that make people’s lives a little easier.

About me Resume

Second Wind Pro

Revamped an NIL agency site and built a sandbox to optimize my workflow.
Job Quest

Leveraging AI to help guide entry-level job seekers in writing their resumes and preparing for interviews.
Suggestion:

Led a 5-person team to address low search relevance by developing and deploying a machine-learning–based ranking model; improved result accuracy by 12%, and resolving key user-experience gaps.

Help me understand

Thinking…

Help me understand, Led a 5-person team to address low search relevance by developing and deploying a machine-learning–based ranking model; improved result accuracy by 12%, and resolving key user-experience gaps.

+1

Got it — let’s break this down in plain language first, then show how an entry-level job seeker can write something similar using the
Problem → Action → Result structure in an ATS-friendly way.

1. What this sentence is really saying (simple explanation)

“Led a 5-person team to address low search relevance by developing and deploying a machine-learning–based ranking model; improved result accuracy by 12%, and resolving key user-experience gaps.”

In simple terms:

Problem: Users weren’t getting good or relevant search results.

What was done: A small team worked together to improve how results were ranked using data and machine learning.

Result: Search results became more accurate (12% better), and user frustrations were reduced.

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Guild Gaming

Turning post-event chaos into clear actionable insights, so organizers aren’t left guessing.
Baseball Little League

From around 300 weekly emails and text messages to a space where coaches and parents communicate seamlessly.

Suggestion:

Led a 5-person team to address low search relevance by developing and deploying a machine-learning–based ranking model; improved result accuracy by 12%, and resolving key user-experience gaps.

Thinking…

Help me understand, Led a 5-person team to address low search relevance by developing and deploying a machine-learning–based ranking model; improved result accuracy by 12%, and resolving key user-experience gaps.

Got it — let’s break this down in plain language first, then show how an entry-level job seeker can write something similar using the
Problem → Action → Result structure in an ATS-friendly way.

1. What this sentence is really saying (simple explanation)

“Led a 5-person team to address low search relevance by developing and deploying a machine-learning–based ranking model; improved result accuracy by 12%, and resolving key user-experience gaps.”

In simple terms:

Problem: Users weren’t getting good or relevant search results.
What was done: A small team worked together to improve how results were ranked using data and machine learning.
Result: Search results became more accurate (12% better), and user frustrations were reduced.

Google Careers MIT Careers Harvard Extension

Ask me or search for anything...

Second Wind Pro

Job Quest

Guild Gaming

Baseball Little League