Leading a team of backend engineers that developed and scaled API with a focus on A/B tests. Typical tasks included validating experimental designs, preparing database schemas, analyzing performance complexity, writing API specifications, implementing features, reviewing peer code, and investigating production issues.

Headed a distributed team of software developers, designers, and QA. Mentored PHP and JavaScript developers. Created architectural blueprints to satisfy business requirements. Monitored and adapted AWS infrastructure for reliable operations.

Teaching a graduate-level elective course on Deep Learning with Neural Networks. Covered topics include Convolutional Neural Networks, Recurring Neural Networks, Generative Adversarial Networks, and Ensemble Learning.

Ideated and developed a model that forecasts demand for pet services. The project consists of a feature extraction pipeline, a boosted ensemble of decision trees, and a suite of metrics for performance measurement. Built a self-service analytics dashboard for validating the results of customer-facing A/B tests. Statistical models applied include t-tests, linear regressions, and linear logistic classifiers.