10 Proven Ways to Quantify Your Data Science Impact

Turn yourself into a top candidate

By now I’ve reviewed a little over 100 resumes—both as a hiring manager and as a Data Science coach.

And this is the most significant element that has helped my mentees take their resumes from generic to one that actually landed interviews:

Quantifying their accomplishments.

It may seem like a small change, but it’s so incredibly effective at making your accomplishments more memorable and impressive.

Why? It’s all rooted in human psychology. Information is easier to process and ambiguity is reduced when numbers are present.

But even though by now, most people understand the importance of quantifying their impact, there is a big stretch between knowing and actually doing.

And during one of my bi-weekly AMAs, someone asked a great question that got me thinking about how data scientists often limit themselves when approaching this task:

Thank you for the great question Jonah!

It's easy to lean on business metrics like revenue and growth when quantifying accomplishments.

But that’s not your only option.

Today, I'll share 10 ways (with examples) to quantify your accomplishments—whether your work directly impacts the business side or focuses on technical or research areas that don’t tie directly to revenue.

Let’s get to it!

1. Revenue, Profit, or Sales Generated

Ask Yourself: How much revenue or profit did my work generate? Did I help increase sales?

Before:

Developed a customer recommendation engine to improve user experience.

After:

Developed a recommendation engine that increased daily sales by 15%, generating an additional $200K in annual revenue.

2. Model Accuracy and Performance

Ask Yourself: How much did I improve the accuracy, precision, or recall of a model?

Before:

Developed a classification model for customer segmentation.

After:

Increased classification accuracy by 10%, boosting customer segmentation effectiveness and driving 20% higher engagement.

3. Time Savings or Efficiency Gains

Ask Yourself: How much time did I save the team or the company? How did I improve efficiency?

Before:

Automated the monthly reporting process.

After:

Automated the reporting process, reducing manual effort by 60% and saving the team 10 hours per week.