Growth Engineer
Growth engineers sit at the intersection of product, data, and engineering, designing experiments that move north-star metrics. Their daily English covers writing experiment briefs, presenting statistical results to product managers, and communicating funnel findings across functions. This path builds the precise vocabulary needed to run, document, and discuss growth experiments with confidence.
Topics covered
- A/B testing & experimentation
- Funnel analysis
- Activation & retention
- Product-led growth
- Statistical significance
- Experiment documentation
Vocabulary spotlight
4 terms every Growth Engineer should know in English:
The single primary metric that best captures the core value a product delivers to users
"Our north-star metric shifted from signups to weekly active users after the PLG pivot."
A segment of users deliberately excluded from an experiment to serve as a control baseline
"We kept a 10% holdout group to measure the long-term effect of the onboarding change."
The point in a conversion funnel where users stop progressing to the next step
"The biggest funnel drop-off is between the pricing page and checkout — 68% abandon there."
To roll out the winning variant of an A/B test to 100% of users after a statistically significant result
"We achieved 95% confidence on day 14, so we shipped the winner to production."
📚 Vocabulary Reference
Key terms organised by category for Growth Engineers:
Experimentation
Funnel & Conversion
Product-Led Growth
Data & Analysis
Recommended exercises
Real-world scenarios you'll practise
- Writing an experiment brief for a new onboarding A/B test and presenting it in a cross-functional review.
- Reporting statistically significant results to a product manager — explaining p-values and confidence intervals in plain English.
- Running a retro on a failed experiment — communicating learnings without blame and proposing next steps.
- Presenting a funnel analysis to stakeholders, highlighting the highest-impact drop-off point and the recommended fix.