Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Science Consultant, AWS Professional Services

Amazon
Bristol
1 week ago
Create job alert
Senior Data Science Consultant, AWS Professional Services

Job ID: 2960371 | AWS EMEA SARL (UK Branch)


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.


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.


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


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Science Consultant, AWS Professional Services

Data Engineering Consultant, AWS Professional Services

Principal Data Science Consultant – Gen AI Specialist

Sr Data Architect, Data Lake & Analytics, ProServe SDT North

Senior Consultant Data Scientist

Senior Consultant Data Scientist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.