Presales Data Science Architect – AWS Cloud

Key Skills

Deep Learning, Machine learning techniques, Natural Language Processing (NLP), Natural Language Understanding-NLU, PySpark, Python Programming, SQL, Statistical modeling, TensorFlow

Job Description

Job Summary:

In this role you will be helping to grow the Rackspace Cloud data practice.  You will be the expert in the region and support the sales of our data projects on AWS Cloud.  Our Presales Data Architects are experienced technologists with technical depth and breadth, along with strong interpersonal skills. In this role, you will work directly with our sales team to propose solutions to customers to achieve business outcomes using AWS Cloud. 

This is a solutions pre-sales role that places significant emphasis on consultative engagements with a wide range of customer stakeholders, 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 toestablish Rackspace credentials as a partner that can help assess, plan and execute the required data transformation or modernization.

Work Location: Remote

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.