Data Scientist, AWS Industries...

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 1.
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.
2. 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. 3.
Create and deliver best practice recommendations, tutorials, blog
posts, publications, sample code, and presentations adapted to
technical, business, and executive stakeholders. 4. 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. BASIC
QUALIFICATIONS 1. 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. 2. 3+ years of machine
learning/statistical modeling data analysis tools and techniques,
and parameters that affect their performance experience. 3.
Experience applying theoretical models in an applied environment.
4. Bachelor's degree in a quantitative field such as statistics,
mathematics, data science, business analytics, economics, finance,
engineering, or computer science. PREFERRED QUALIFICATIONS 1. PhD
in a quantitative field such as statistics, mathematics, data
science, business analytics, economics, finance, engineering, or
computer science. 2. 5+ years of machine learning/statistical
modeling data analysis tools and techniques, and parameters that
affect their performance experience. 3. Hands-on experience with
deep learning (e.g., CNN, RNN, LSTM, Transformer). 4. 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/accommodationsfor more
information. If the country/region you’re applying in isn’t listed,
please contact your Recruiting Partner. Posted: April 3, 2024
(Updated 4 days ago) #J-18808-Ljbffr