We are expanding our efforts into complementary data technologies for decision support in areas that capitalize on intelligent applications enabled with computational learning. Our interests are in enabling intelligent applications and corresponding computation learning processing on large and low latent data sets with elastic cloud architecture techniques on premise.To that end, this role will engage with team counterparts in exploring and deploying technologies for engineering features and creating algorithms that result in models incorporated into intelligent applications. Application use cases are expected to focus on core aspects of our business such as risk management and customer experience. Responsibility also includes coding, testing, and documentation of new or modified scalable analytic data systems including automation for deployment and monitoring. This role participates along with team counterparts to architect an end-to-end framework developed on a group of core data technologies. Other aspects of the role include developing standards and processes for computational learning projects and initiatives.