Title: Big Data Machine Learning Engineer@ Chicago, IL
Terms of Hire: Full Time.
Salary: $Open+ Benefits.
The candidate can also work from any of these locations:
ABOUT THE JOB
The Decision Sciences team is part of the Enterprise Payments and Analytics organization. Its mission is to lead Client’s journey to become an innovative, data driven enterprise by building advanced analytics solutions for solving business problems. Our experienced team of AI/ML and Data Science practitioners focuses on engaging, enabling, and empowering decision-makers across the enterprise by developing, managing and supporting advanced analytics products and scalable digital solutions, such as real time and on demand predictive models and prescriptive analytics, and continuously researching, specifying, and deploying next-generation analytics capabilities. We are an internal consulting and services organization that works directly with users across the firm, including Lines of Businesses and partners in Enterprise Strategy, Marketing, Data Analytics, and Enterprise Architecture, to facilitate the development of innovative solutions that help Client compete and win with analytics. The Big Data ML Engineer fills a critical data, analytics, technology support, and innovation role for the business analytics and advanced analytics functions within the organization. The Engineer is primarily responsible for end-user product development, deployment in production framework, data analytics technical support as well as leveraging best tools and techniques, and end-user training of new emerging analytics open source technologies. S/he is also the primary conduit for identifying, researching, and evaluating new and innovative technologies that enhance the organization’s enterprise analytics and advanced analytics capabilities.
ESSENTIAL JOB FUNCTIONS
The ML Engineer works both independently and in collaboration with a cross-functional team of Data scientists and solution system architects to effectively develop, deploy, monitor, manage, and support AI/ML models and advanced analytics technology, data infrastructures, and underlying analytics use cases—primarily focused around open source technologies including cloud infrastructures. This individual evaluates short/long-term business needs required to support Client business goals and priorities and works to ensure Advanced analytics solutions are built and deployed in an effective and efficient manner on Client Enterprise systems. Under the guidance of the Group’s Director and in cooperation with partners in decision science, technology, and data the Engineer will coordinate the development of on-premise and cloud-based analytical non-production and production infrastructure and tools providing computational and statistical capabilities to enhance business results and monetize on Client data assets for business decision management solutions. The Engineer will be working closely with data scientists, data mining experts, and business partner supporting the design of experiments and analytics, data sampling and mining, verification of data quality and information integrity, and best practices around the development and deployment of predictive/prescriptive models, DevOps operational systems and practices, and data visualization solutions. The Engineer has responsibility for advising data scientists, Agile project teams, and solution architects in the integration of analytical models/methods into decision management solutions. The Engineer will assist peers in best practices and in the selection and integration of appropriate tools to support required analytic products in close coordination with the organization’s AI/AutoML analytics, digital intelligence engineers, solution/data architects, data integration developers, and data science community ensuring tight integration of functionality and toolsets.
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All applications will be kept strictly confidential and once shortlisted, our team will be in touch with you for further discussions.