Kasey Mallette

At Dell Technologies, I built Python and SQL forecasting systems for enterprise capacity planning across 1,000+ applications, turning observability records, logs, UI JSON, and application metadata into model-ready time series.

I developed forecasting workflows using ARIMA, Prophet, exponential smoothing, weighted moving averages, and consumption baselines, reducing forecast error by 15%. I also designed anomaly detection and monitoring workflows that surfaced changepoints, usage spikes, missing forecasts, decommissioned applications, and forecast-versus-actual mismatches.

I deployed and maintained production ML and data pipelines with Airflow, Docker/BYOC, SQL stored procedures, and database writeback logic. As product and technical lead for the data-science workstream, I defined requirements, planned implementations, delegated work, and mentored junior data scientists.

Independently, I build applied AI systems including Wax, a human-in-the-loop music recommendation and playlist-generation product, and GPT-4o persona systems with consistent voice, identity, and conversational behavior. I also create generative AI storytelling, image, video, and web experiences.