National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Data Scientist, Data Intelligence, Professional Services GCR

Amazon
London
1 day ago
Applications closed

Related Jobs

View all jobs

Sr. Data Scientist / Machine Learning Engineer - GenAI & LLM

Sr. Data Scientist / Machine Learning Engineer - GenAI

Sr. Data Scientist / Machine Learning Engineer - GenAI & LLM...

Data Scientist - AWS Professional Services

Senior Data Scientist - AWS Professional Services

Staff Data Scientist

AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.

The Amazon Web Services Professional Services team is looking for a Data Scientist, this role plays a crucial role in delivering the generative artificial intelligence (GenAI) solutions for our clients. This position requires a deep understanding of machine learning, natural language processing, and generative models, combined with problem-solving skills and a passion for innovation.

Key job responsibilities

  1. Generative AI Model Development:
    -Design and develop generative AI models, including language models, image generation models, and multimodal models.
    -Explore and implement advanced techniques in areas such as transformer architectures, attention mechanisms, and self-supervised learning.
    -Conduct research and stay up-to-date with the latest advancements in the field of generative AI.

    2. Data Acquisition and Preprocessing:
    -Identify and acquire relevant data sources for training generative AI models.
    -Develop robust data preprocessing pipelines, ensuring data quality, cleanliness, and compliance with ethical and regulatory standards.
    -Implement techniques for data augmentation, denoising, and domain adaptation to enhance model performance.

    3. Model Training and Optimization:
    -Design and implement efficient training pipelines for large-scale generative AI models.
    -Leverage distributed computing resources, such as GPUs and cloud platforms, for efficient model training.
    -Optimize model architectures, hyperparameters, and training strategies to achieve superior performance and generalization.

    4. Model Evaluation and Deployment:
    -Develop comprehensive evaluation metrics and frameworks to assess the performance, safety, and bias of generative AI models.
    -Collaborate with cross-functional teams to ensure the successful deployment and integration of generative AI models into client solutions.

    5. Collaboration and Knowledge Sharing:
    -Collaborate with data engineers, software engineers, and subject matter experts to develop innovative solutions leveraging generative AI.
    -Contribute to the firm's thought leadership by presenting at conferences, and participating in industry events.

    About the team
    AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.

    About AWS

    Diverse Experiences
    AWS values diverse experiences. Even if you do not meet all of the 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.

    AWS is committed to a diverse and inclusive workplace to deliver the best results for our customers. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status; we celebrate the diverse ways we work. For individuals with disabilities who would like to request an accommodation, please let us know and we will connect you to our accommodation team.
  • Master's or Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.
  • 4+ years of experience in developing and deploying machine learning models, with a strong focus on generative AI techniques.
  • Proficiency in programming languages such as Python, PyTorch, or TensorFlow, and experience with deep learning frameworks.
  • Strong background in natural language processing, computer vision, or multimodal learning.
  • Ability to communicate technical concepts to both technical and non-technical audiences.
  • Experience with large language models, such as Claude, GPT, BERT, or T5.
  • Familiarity with reinforcement learning techniques and their applications in generative AI.
  • Understanding of ethical AI principles, bias mitigation techniques, and responsible AI practices.
  • Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and distributed computing frameworks (e.g., Apache Spark, Dask).
  • Strong problem-solving, analytical, and critical thinking skills.
  • Strong communication, collaboration, and leadership skills.

    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 visithttps://amazon.jobs/content/en/how-we-hire/accommodationsfor more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

    #J-18808-Ljbffr
National AI Awards 2025

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.

AI Jobs UK 2025: 50 Companies Hiring Now

Bookmark this guide – we refresh it every quarter so you always know who’s really scaling their artificial‑intelligence teams. Artificial intelligence hiring has roared back in 2025. The UK’s boosted National AI Strategy funding, record‑breaking private investment (£18.1 billion so far) & a fresh wave of generative‑AI product launches mean employers are jockeying for data scientists, ML engineers, MLOps specialists, AI product managers, prompt engineers & applied researchers. Below are 50 organisations that have advertised UK‑based AI vacancies in the past eight weeks or formally announced growth plans. They’re grouped into five easy‑scan categories so you can jump straight to the kind of employer – & culture – that suits you. For each company you’ll find: Main UK hub Example live or recent vacancy Why it’s worth a look (tech stack, culture, mission) Use the internal links to browse current vacancies on ArtificialIntelligenceJobs.co.uk – or set up a free job alert so fresh roles land in your inbox.

Return-to-Work Pathways: Relaunch Your AI Career with Returnships, Flexible & Hybrid Roles

Stepping back into the workplace after a career break can feel like embarking on a whole new journey—especially in a cutting-edge field such as artificial intelligence (AI). For parents and carers, the challenge isn’t just refreshing your technical know-how but also securing a role that respects your family commitments. Fortunately, the UK’s tech sector now boasts a wealth of return-to-work programmes—from formal returnships to flexible and hybrid opportunities. These pathways are designed to bridge the gap, equipping you with refreshed skills, confidence and a supportive network. In this comprehensive guide, you’ll discover how to: Understand the booming demand for AI talent in the UK Leverage transferable skills honed during your break Overcome common re-entry challenges Build your AI skillset with targeted training Tap into returnship and re-entry programmes Find flexible, hybrid and full-time AI roles that suit your lifestyle Balance professional growth with caring responsibilities Master applications, interviews and networking Whether you’re returning after maternity leave, eldercare duties or another life chapter, this article will equip you with practical steps, resources and insider tips.

LinkedIn Profile Checklist for AI Jobs: 10 Tweaks That Triple Recruiter Views

In today’s fiercely competitive AI job market, simply having a LinkedIn profile isn’t enough. Recruiters and hiring managers routinely scout for top talent in machine learning, data science, natural language processing, computer vision and beyond—sometimes before roles are even posted. With hundreds of applicants vying for each role, you need a profile that’s optimised for search, speaks directly to AI-specific skills, and showcases measurable impact. By following this step-by-step LinkedIn for AI jobs checklist, you’ll make ten strategic tweaks that can triple recruiter views and position you as a leading AI professional. Whether you’re a fresh graduate aiming for your first AI position or a seasoned expert targeting a senior role, these actionable changes will ensure your profile stands out in feeds, search results and recruiter queues. Let’s dive in.