You Will:

• This is client facing, pre-sales technologist that works with designated accounts and acts as a technical advocate for Rackspace clients. 
• You are responsible for understanding clients’ business requirements as they pertain to Data solutions, qualifying opportunities and creating designs that match the requirements with appropriate products, managed and professional services.
• Is considered a thought leader and develops IP & collateral for data and analytics.
• 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 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 Administrative Overhead.
• 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

Technical Requirements:

• Has experience with traditional, as well as modern Machine Learning/Statistical techniques, including Regression, Classification, Ensemble Methods, Deep Learning
• Communicate complex models and analysis in a clear and precise manner coupled with actionable conclusions and recommendations.
• You have strong problem solving, analytic, decision-making capabilities and excellent communication with interpersonal skills.
• You have hands-on experience with Python, PySpark, SQL and the ability to write reusable and efficient code to automate machine learning pipeline and data processes.
• You have experience with deep learning library like TensorFlow and/or PyTorch as well as experience with Spark and/or Hadoop.
• Have strong knowledge of Statistics, Machine Learning, Deep Learning and NLP/NLU.
• You bring strong engineering mindset and exposure to software engineering principles, Agile methodologies.
• 5+ years of experience as a data scientist and have applied industry experience in NLP/NLU, Forecasting and Anomaly detection solution development. 

Other Requirements

• Highly motivated self-starter and team player and demonstrated success in prior roles.
• Track record of success working through technical challenges within enterprise organizations
• Ability to prioritize deals, training, and initiatives through highly effective time management.
• Excellent problem solving, analytical, presentation, and whiteboarding skills.
• Track record of success dealing with ambiguity (internal and external) and working collaboratively with other departments and organizations to solve challenging problems.
• Strong knowledge of technology and industry trends that affect data analytics decisions for enterprise organizations.

Education:

• Bachelor’s degree in Engineering, Computer Science, Information Systems, or Business required
• Experience may substitute for the degree requirement at a rate of 3 years’ experience for 1 year of education.
• High school diploma or equivalent required

Sponsorship:

• This role is not sponsorship eligible