Data Scientist, AWS Industries

Amazon Jobs; London; On-site; GBP 70,000 - 90,000; Full time

Job summary

A leading cloud technology company is seeking a Data Scientist to collaborate on generative AI solutions. You will work with AI/ML teams to design and implement innovative algorithms, engage directly with customers, and contribute to best practices and learning resources. Ideal candidates should have substantial experience in data science and machine learning.

Qualifications

• 5+ years of data scientist experience.
• 3+ years of experience with data querying and scripting languages.
• Hands-on experience with deep learning techniques.

Responsibilities

• Collaborate with AI/ML teams to evaluate generative AI algorithms.
• Interact with customers to implement generative AI solutions.
• Deliver best practices and tutorials for technical stakeholders.

Skills

Data querying languages (e.g. SQL)

Scripting languages (e.g. Python)

Machine learning/statistical modeling

Deep learning (e.g., CNN, RNN)

Large Language Models (LLMs)

Education

Bachelor's degree in a quantitative field

PhD in a quantitative field

Job description

Overview

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? The AWS Industries Team at AWS helps AWS customers implement Generative AI solutions and realize transformational business opportunities in strategic industry verticals. This is a team of data scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI.

The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and build applications to launch these solutions at scale. The AWS Industries team provides guidance and implements best practices for applying generative AI responsibly and cost efficiently.

You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

In this Data Scientist role you will be capable of using GenAI and other techniques to design, evangelize, and implement and scale cutting-edge solutions for never-before-solved problems.

Responsibilities

• Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate cutting-edge generative AI algorithms and build ML systems to address real-world challenges
• Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production
• Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations adapted to technical, business, and executive stakeholders
• Provide customer and market feedback to Product and Engineering teams to help define product direction

About the team

Diverse Experiences: Amazon 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.

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.

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 and 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.

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.

AWS Professional Services engage in a wide variety of projects for customers and partners, providing collective experience from across the AWS customer base. We are obsessed about delivering success for the Customer. Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based upon customer needs.

Qualifications

• 5+ years of data scientist experience and 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
• Experience applying theoretical models in an applied environment
• Bachelor’s degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
• PhD in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
• 5+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
• Hands on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer)
• Prior experience in training and fine-tuning of Large Language Models (LLMs) and knowledge of AWS platform and tools

Amazon is an equal opportunities employer. We believe 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 the accommodations page for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.