Data Scientist Cover Letter Example

ShopAI's personalisation challenge is one I have worked on from the other side: building the model that has to generalise across customers with wildly different purchase histories while staying fast enough for real-time inference. I would like to bring that experience to your team.

At my current company I built a real-time personalisation model that increased add-to-cart rate by 11% across 2M monthly active users. The hard part was not the model — it was the feature store design. We needed product embeddings that could be updated without a full retraining cycle. Getting that architecture right took longer than the model itself, but it is what makes the system maintainable 18 months later.

I also replaced a rule-based fraud detection system with an XGBoost model that reduced false positive rate by 65% while holding fraud recall at 98%. I presented the model to the risk committee monthly for a year — not the statistics, but the business consequences: X fewer false positives per day means Y hours of manual review saved and Z customers who are not wrongly blocked. Translating the model into those terms was as important as building it.

I have been following your engineering blog, particularly the post on handling cold-start in recommendation systems. I have an approach to that problem from my current work that I would enjoy discussing — either in writing or on a call, whatever is more useful to you.