.This is a solutions pre-sales role that places significant emphasis on consultative engagements with a wide range of customer stakeholders, including Business Owners, Business Analytics, Data Engineering teams, Application Development, End Users, and Management teams.Successful candidates will be adept at evangelizing the Rackspace Data Services value proposition – across Professional Services and Managed Services; aligning it to each unique set of customer challenges and articulating the business benefits that can be delivered.A key aspect of the role is to engage with customers early in their transformation journey to establish Rackspace credentials as a partner that can help assess, plan, and execute the required data transformation or modernization.Key Responsibilities:Sells and positions implementation and advisory services primarily in their assigned LOB, but also understands and advises clients on where other strategic and advisory services fit their needs.Client Facing Sales Support – Works with the sales account team, interfacing directly with the Rackspace prospects and customers.Builds trusted advisor relationships, understanding client's business challenges and proposing solutions.Develops High Level Designs and Architectures – Creates and documents architectures that address client business problems which can be used to ensure a smooth transition from presales to delivery.Create Proposals – Develop proposals, SOWs (Statements Of Work), business cases, and RFP responses.Sales Planning – Work with management and sales teams to develop account prioritization and support strategies that will ensure a long-term trusted relationship status.Partner Relationship Management – Develop healthy and trusted relationships with key partners in the geography.Intellectual Property Development – Contribute to the development of Rackspace intellectual property and industry recognition (white papers, speaking engagements, etc.).Administrative Overhead – Respond to email, phone calls, complete timesheets in a timely manner, expense reports, and status reports as required.Training – Develop and execute a professional plan that will enhance skills.Contribute to sales process improvement, including developing knowledge bases, creating sales tools, and mentoring other Solutions Architects.Required Experience:8 - 11 years of experience in the field of role required.Experience with traditional, as well as modern Machine Learning/Statistical techniques, including Regression, Classification, Ensemble Methods, Deep Learning.Ability to communicate complex models and analysis in a clear and precise manner, coupled with actionable conclusions and recommendations.Strong problem solving, analytic, decision-making capabilities, and excellent communication with interpersonal skills.Hands-on experience with Python, PySpark, SQL, and the ability to write reusable and efficient code to automate machine learning pipeline and data processes