Energy AI/ML Data Scientist on AWS

Amazon Web Services, Inc.; Houston (TX); On-site; USD 154,000 - 208,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Web Services, Inc. in Houston seeks a Data Scientist within AWS Professional Services' Energy segment to design, build, validate, and deploy end-to-end ML/DL solutions on AWS.

You will work with enterprise and public-sector customers to translate business challenges into scalable cloud AI capabilities. In this role you will collaborate with data teams, IT, and product owners to assess data, build and validate models, and communicate results.

Qualifications

• 7+ years of technical specialist, design and architecture experience.
• 3+ years of cloud-based solutions experience in AWS or equivalent.
• 7+ years of customer-facing, large-scale project management experience.
• 5+ years of cloud architecture and solution implementation experience.
• Bachelor's degree, or 7+ years of professional or military experience.

Responsibilities

• Leading and developing a high-performing team of Account Executives and Cloud Architects.
• Developing and supporting sales strategies to meet targets and drive revenue.
• Managing customer relationships with high satisfaction and identifying new opportunities.
• Guiding sellers with deep AWS knowledge to propose optimal solutions.
• Monitoring KPIs and forecasting to optimize operations and manage risk.

Skills

Leadership

Account management

Sales strategy

Cloud architecture

Stakeholder management

Data-driven decision making

Communication

Education

Bachelor's degree or equivalent experience

Job description

Amazon Web Services, Inc. in Houston seeks a Data Scientist within AWS Professional Services' Energy segment to design, build, validate, and deploy end-to-end ML/DL solutions on AWS.

You will work with enterprise and public-sector customers to translate business challenges into scalable cloud AI capabilities. In this role you will collaborate with data teams, IT, and product owners to assess data, build and validate models, and communicate results.