At a Glance
- Tasks: Join a dynamic team to develop and implement cutting-edge generative AI solutions for real-world challenges.
- Company: AWS is a leader in cloud computing, driving innovation in AI and machine learning.
- Benefits: Enjoy flexible work options, competitive salary, and opportunities for professional growth.
- Why this job: Be part of transformative projects that make a significant impact on businesses and society.
- Qualifications: 2+ years as a data scientist with experience in SQL, Python, and machine learning techniques.
- Other info: Diversity and inclusion are core values at Amazon; all backgrounds are encouraged to apply.
The predicted salary is between 43200 - 72000 £ per year.
Job ID: 2916032 | AWS EMEA SARL (UK Branch) – F93
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 for AWS customers in the most 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.
Key job 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 stakeholder.
- Provide customer and market feedback to Product and Engineering teams to help define product direction.
BASIC QUALIFICATIONS
- 2+ 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.
PREFERRED QUALIFICATIONS
- 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 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 committed to a diverse and inclusive workplace. 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.
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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Data Scientist, AWS Industries employer: Amazon
Contact Detail:
Amazon Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist, AWS Industries
✨Tip Number 1
Familiarise yourself with the latest trends in Generative AI and machine learning. Being able to discuss recent advancements or case studies during your interactions with the team will demonstrate your passion and knowledge, making you a more attractive candidate.
✨Tip Number 2
Engage with the AWS community by attending webinars, workshops, or meetups focused on AI and machine learning. Networking with professionals in the field can provide valuable insights and potentially lead to referrals within the company.
✨Tip Number 3
Prepare to showcase your problem-solving skills through practical examples. Be ready to discuss specific projects where you've applied machine learning techniques to solve real-world problems, as this aligns closely with the responsibilities of the role.
✨Tip Number 4
Research AWS's existing generative AI solutions and think critically about how you could contribute to their development. Having ideas ready to share during interviews can set you apart and show your proactive approach to the role.
We think you need these skills to ace Data Scientist, AWS Industries
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and qualifications required for the Data Scientist position. Familiarise yourself with generative AI concepts and how they apply to real-world problems.
Tailor Your CV: Customise your CV to highlight relevant experience in data science, machine learning, and any specific tools mentioned in the job description, such as SQL, Python, or deep learning frameworks. Use keywords from the job listing to ensure your CV stands out.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and machine learning. Discuss specific projects where you've applied generative AI or similar technologies, and explain how your skills align with the needs of the AWS Industries team.
Showcase Your Projects: If applicable, include links to your portfolio or GitHub repository where you have showcased relevant projects. Highlight any experience with large language models or AWS tools, as this will demonstrate your hands-on expertise.
How to prepare for a job interview at Amazon
✨Showcase Your Technical Skills
Be prepared to discuss your experience with data querying languages like SQL and scripting languages such as Python. Highlight specific projects where you've applied machine learning techniques, especially in generative AI.
✨Understand the Business Context
Demonstrate your ability to interact with customers by discussing how you would approach understanding their business problems. Prepare examples of how you've previously helped clients implement AI solutions.
✨Prepare for Problem-Solving Questions
Expect to face scenario-based questions that assess your problem-solving skills. Think about how you would design experiments or optimise models in real-world situations, particularly in relation to generative AI.
✨Communicate Clearly and Effectively
Since you'll be delivering briefings and tutorials, practice explaining complex concepts in simple terms. Be ready to adapt your communication style to suit technical, business, and executive stakeholders.