Presales Data Science Lead

hace 1 mes

Xico, México Rackspace A tiempo completo

This is a solutions pre-sales role that places significant emphasis on consultative engagements with a wide range of customer stakeholders, Business Owners, Data Engineering teams, Application Development, End Users and Management teams.

Key Responsibilities include:

  • Selling and positioning implementation and advisory services primarily in their assigned LOB, but also understanding and advising clients on where other strategic and advisory services fit their needs.
  • Client Facing Sales Support - Working with sales account teams, interfacing directly with Rackspace prospects and customers.
  • Building trusted advisor relationships, understanding client's business challenges and proposing solutions.
  • Developing High Level Designs and Architectures - Creating and documenting architectures that address client business problems which can be used to ensure a smooth transition from presales to delivery.
  • Creating Proposals - Developing proposals, SOWs (Statements Of Work), business cases and RFP responses.
  • Sales Planning - Working with management and sales teams to develop account prioritization and support strategies that will ensure a long-term trusted relationship status.
  • Partner Relationship Management - Developing healthy and trusted relationships with key partners in the geography.
  • Intellectual Property Development - Contributing to the development of Rackspace intellectual property and industry recognition (white papers, speaking engagements etc.).
  • Training - Developing and executing a professional plan that will enhance skills.
  • Contributing to sales process improvement, including developing knowledge bases, creating sales tools, and mentoring other Solutions Architects.

Required Experience includes:

  • 8 - 11 years of experience in the field of data science required.
  • Experience with traditional, as well as modern Machine Learning/Statistical techniques, including Regression, Classification, Ensemble Methods, Deep Learning.
  • Communicating 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.
  • Experience with deep learning library like TensorFlow and/or PyTorch as well as experience with Spark and/or Hadoop.
  • Strong knowledge of Statistics, Machine Learning, Deep Learning and NLP/NLU.
  • 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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