Technical leader of Data Science & Engineering for early and growth stage companies. I specialize in getting things done, removing impediments, rapid builds, adoption of best practices — and in positively propagating this approach throughout the organization. Reporting to VP Engineering, CTO, or CEO across domains including IoT, smarthomes, robotics and software. * Built and run combined DS/ML/Eng teams of up to 13 ICs with add'l manager* Hands-on in emerging ML tech and custom ML algorithms* Domain Experience: Smarthomes & IoT, computer vision, robotics/embedded, internal operations/finance, mobile apps* Designing APIs to deploy data/ML assets to production (OpenAPI specs and tooling)* Software: agile/iterative, design patterns, refactoring, unit and integration testing, containerization, version control, CI/CD* Private equity operational experience focused on injecting ML and Engineering best practices into portfolio investments across enterprise, consumer* AI/ML: broad base with specialization in recurrent networks, transformers, custom/masked loss functions; also, optimization of (non-neural network) algorithm parameters, learning in spiking neural networks * Data Science-specific: data architecture/inventory, data/ML pipeline automation, staged data lake designs; experience with Databricks/MLflow/Delta LakeNamed inventor on 35 patents, and author on 36 peer reviewed scientific papers (sole author on two). Academic background in computational and cognitive neuroscience, with a focus on models of human brain mechanisms of learning and attention.Patents for: * Custom ML algorithm for robust open-world computer vision (US Patent No. 10,282,849)* Adaptive self-reconfiguring UI/UX for Robots based on attached peripherals or configuration changes (US Pat. No. 9.242,372)* Intercepting and learning from remote controls in Smarthomes (US Pat. No. 9,630,317)* Resolving conflict in robotic control through learning (US Pat. No. 9,296,101)