Dear Hiring Manager,
I am applying for my first full-time data scientist role after completing project work that used Python, SQL, scikit-learn, BigQuery, dbt, and experiment design. My strongest evidence is a recent portfolio project where I analysed activation cohorts, corrected a biased funnel read, and changed onboarding priorities for a 2.8M-user product.
I know an entry-level hire has to be easy to coach and useful quickly. Your team needs statistical judgement, SQL fluency, experiment design, and clear product recommendations, and my strongest examples sit in that exact area. I would use this letter to show the connection with one specific project, the constraints I worked under, and the judgement I brought to the decision points.
A recent example is that I analysed activation cohorts, corrected a biased funnel read, and changed onboarding priorities for a 2.8M-user product. That work required Python, SQL, scikit-learn, BigQuery, dbt, and experiment design, but the more important point is how I made decisions, explained tradeoffs, and followed the result through after release.
I would be glad to discuss the project work, tradeoffs, and feedback that shaped it. data science screens test whether evidence changes decisions, so I would keep the letter concise, evidence-led, and tied to the outcomes the hiring team is likely to care about.
Yours sincerely, Alex Morgan