Data Scientist · cover letter
[Date]
Dear [Hiring Manager],
Last year I rebuilt a churn model whose AUC sat at 0.71 and could not flag at-risk accounts in time. By reframing the target window and engineering 40 behavioral features, I raised AUC to 0.88 and gave the retention team a 9 day head start, which protected roughly 1.4 million dollars in annual recurring revenue. That is the kind of impact I want to bring to [Company].
I work end to end. I pull and shape data in SQL across warehouse tables, prototype in Python with pandas and scikit-learn, and ship the winning model to production behind a versioned API. On a recommendation project, I ran a two week A/B test on 60,000 users, confirmed an 11 percent lift in click through at 95 percent significance, and wrote the readout that convinced product to roll it out. After launch I added drift and latency monitoring so we caught a feature pipeline break in hours rather than discovering it through a drop in conversion weeks later.
What I value most is making the statistics legible to the people who act on them. I replaced a black box scoring deck with a partial dependence walkthrough that finance could question line by line, and that trust is what got the model funded for a second quarter. I am comfortable owning the full path from a vague business question to a deployed, monitored model.
AUC moved from 0.71 to 0.88 because I reframed the target window, a smaller change than the feature engineering everyone assumes did the work. The notebook and the feature list are both ready whenever you want to see it.
Sincerely,
[Your Name]
[Phone]
[Email]