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Sr. Data Scientist, WWPS ProServe Data and Machine Learning
AMAZON-HQ2 • Arlington, Virginia, United States | Herndon, Virginia, United States • onsite
FULL_TIME
Active
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Job Details
Company
amazon hq2
Location
Arlington, Virginia, United States | Herndon, Virginia, United States
Work Type
onsite
Job Type
FULL_TIME
Posted
January 1, 1970
Description
This position requires that the candidate selected be a US Citizen and must
currently possess and maintain an active TS/SCI security clearance with
polygraph.
The Amazon Web Services Professional Services (ProServe) team is seeking a
skilled Data Scientist to join our team at Amazon Web Services (AWS). Are you
looking to work at the forefront of Machine Learning and AI? Would you be
excited to apply Generative AI algorithms to solve real world problems with
significant impact? In this role, you'll work directly with customers to design,
evangelize, implement, and scale AI/ML solutions that meet their technical
requirements and business objectives. You'll be a key player in driving customer
success through their AI transformation journey, providing deep expertise in
data science, machine learning, generative AI, and best practices throughout the
project lifecycle.
As a Data Scientist within the AWS Professional Services organization, you will
be proficient in architecting complex, scalable, and secure machine learning
solutions tailored to meet the specific needs of each customer. You'll help
customers imagine and scope the use cases that will create the greatest value
for their businesses, develop statistical models and analytical frameworks,
select and train the right models, and define paths to navigate technical or
business challenges. Working closely with stakeholders, you'll assess current
data infrastructure, perform exploratory data analysis, develop
proof-of-concepts, and propose effective strategies for implementing AI and
generative AI solutions at scale. You will design and run experiments, research
new algorithms, extract insights from complex datasets, and find new ways of
optimizing risk, profitability, and customer experience.
The AWS Professional Services organization is a global team of experts that help
customers realize their desired business outcomes when using the AWS Cloud. We
work together with customer teams and the AWS Partner Network (APN) to execute
enterprise cloud computing initiatives. Our team provides assistance through a
collection of offerings which help customers achieve specific outcomes related
to enterprise cloud adoption. We also deliver focused guidance through our
global specialty practices, which cover a variety of solutions, technologies,
and industries.
Key job responsibilities
- Designing and implementing complex, scalable, and secure AI/ML solutions on
AWS tailored to customer needs, including developing statistical models,
performing feature engineering, and selecting appropriate algorithms for
specific use cases
- Developing and deploying machine learning models and generative AI
applications that solve real-world business problems, conducting experiments,
performing rigorous statistical analysis, and optimizing for performance at
scale
- Collaborating with customer stakeholders to identify high-value AI/ML use
cases, gather requirements, analyze data quality and availability, and propose
effective strategies for implementing machine learning and generative AI
solutions
- Providing technical guidance on applying AI, machine learning, and generative
AI responsibly and cost-efficiently, performing model validation and
interpretation, troubleshooting throughout project delivery, and ensuring
adherence to best practices
- Acting as a trusted advisor to customers on the latest advancements in AI/ML,
emerging technologies, statistical methodologies, and innovative approaches to
leveraging diverse data sources for maximum business impact
- Sharing knowledge within the organization through mentoring, training,
creating reusable AI/ML artifacts and analytical frameworks, and working with
team members to prototype new technologies and evaluate technical feasibility
Basic Qualifications: - Bachelor's degree in a quantitative field such as
statistics, mathematics, data science, business analytics, economics, finance,
engineering, or computer science
- 5+ years of data scientist or simil
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