Presales Data Science Architect – AWS Cloud

Key Responsibilities:

• Solutions and positions solutions for customers.
• 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.
• 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 

Qualifications:

• 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.  




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Travel

• As per business requirements

Sponsorship

• This role is not sponsorship eligible
• Candidates need to be legally allowed to work in the US for any employer