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Job Post Details

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Senior Data Science Consultant, AWS Professional Services - job post

AWS EMEA SARL (UK Branch)
(part of Amazon.com)
3.4 out of 5 stars
London
Full-time

Location

London

Full job description

DESCRIPTION

As a Senior Data Science & AI Consultant in AWS Professional Services, you will lead the delivery of cutting-edge artificial intelligence and machine learning solutions for our enterprise customers. You'll drive innovation in Generative AI, shape technical strategy, and serve as a trusted advisor to customers throughout their AI transformation journey.

Key job responsibilities
1. Lead end-to-end delivery of complex AI/ML engagements, from strategic planning through to pre-production deployment and optimisation
2. Architect and implement advanced solutions leveraging AWS's AI/ML services, with particular focus on Generative AI using Amazon Bedrock and SageMaker
3. Provide technical leadership and mentorship to junior consultants while driving best practices across delivery teams
4. Partner with customers to translate business challenges into measurable ML outcomes and clear delivery roadmaps
5. Drive innovation in applied AI/ML, contributing to methodologies and reusable solutions across the practice
6. Influence customer AI strategy through technical expertise and industry insights
7. Lead multi-disciplinary teams and coordinate across stakeholder groups to deliver high-impact AI solutions
8. Provide thought leadership in internal and external engagements
9. Support pre-sales activities to provide technical expertise and review project scoping and risks

This role will be based in our AWS offices in London, Manchester, Bristol or Cambridge, when not at the Customer site.

NB: You will need to be a UK national and able to obtain and maintain a UK Government Security Clearance. Further details found here: https://www.gov.uk/government/publications/united-kingdom-security-vetting-clearance-levels

About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

BASIC QUALIFICATIONS

  • Strong experience in building large scale machine learning or deep learning models and in Generative AI model development
  • Experience in data and machine learning engineering and cloud native technologies
  • Strong experience communicating across technical and non-technical audiences
  • Strong experience facilitating discussions with senior leadership regarding technical / architectural trade-offs, best practices, and risk mitigation
  • Eligibility for the UK Security Clearance

PREFERRED QUALIFICATIONS

  • Master's degree in a quantitative field such as statistics, mathematics, data science, engineering, or computer science
  • Knowledge of the primary AWS services (ec2, elb, rds, route53 & s3)
  • Experience with software development life cycle (sdlc) and agile/iterative methodologies
  • Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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