Applied Scientist
Company: Amazon.com
Location: Newark
Posted on: October 29, 2024
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Job Description:
At Audible, we believe stories have the power to transform
lives. It's why we work with some of the world's leading creators
to produce and share audio storytelling with our millions of global
listeners. We are dreamers and inventors who come from a wide range
of backgrounds and experiences to empower and inspire each other.
Imagine your future with us.ABOUT THIS ROLEIn this role, you'll
employ scalable cutting-edge machine learning (ML), deep learning
(DL), and Natural Language Processing (NLP) techniques to detect
and predict fraudulent activities, enhance fraud investigation
capabilities, and develop advanced fraud protection and defense
mechanisms. You'll leverage these technologies to analyze complex
patterns in transaction data, identify anomalies, and create
predictive models that can anticipate potential fraud before it
occurs. Your work will be crucial in safeguarding the company's
assets, protecting customers from financial harm, and maintaining
the integrity of our systems. You'll translate intricate fraud
patterns into actionable insights, enabling rapid response to
emerging threats and informing critical business decisions related
to risk management. You'll operate in an agile environment in which
we own and collaborate on the life cycle of research, design, and
model development of relevant projects.As an Applied Scientist, you
will...- Protect Audible's customers and content creators against
the onslaught of AI-generated fraud- Develop Amazon-scale data
engineering & modeling pipelines- Imagine and invent before the
business asks, and create groundbreaking fraud detection and
mitigation solutions using cutting-edge approaches- Work closely
with other data scientists, ML experts, engineers as well as
business across the globe, and on cross-disciplinary efforts with
other scientists within Amazon- Contribute to the growth of the
Audible Data Science team by sharing your ideas, intellectual
property and learning from othersABOUT AUDIBLEAudible is the
leading producer and provider of audio storytelling. We spark
listeners' imaginations, offering immersive, cinematic experiences
full of inspiration and insight to enrich our customers daily
lives. We are a global company with an entrepreneurial spirit. We
are dreamers and inventors who are passionate about the positive
impact Audible can make for our customers and our neighbors. This
spirit courses throughout Audible, supporting a culture of
creativity and inclusion built on our People Principles and our
mission to build more equitable communities in the cities we call
home.BASIC QUALIFICATIONS- MS in one of the following disciplines:
Computer Science, Statistics, Data Science, Economics, Applied
Math, Operational Research or a related quantitative field +5 yrs
relevant experience; or PhD- Fluency in Python, SQL or similar
scripting languages and skilled at Java, C++, or other programing
languages- Experience in algorithm development- Depth and breadth
in state-of-the-art machine learning technologies- Machine Learning
Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step
Functions) or similar cloud-platforms- Big Data Engineering with
Spark / AWS EMR & GluePREFERRED QUALIFICATIONS- Domain knowledge of
comparable products (digital, retail)- Publications at top-tier
peer-reviewed conferences or journals in one of those areas
(natural language processing/understanding, deep learning, machine
learning, or speech processing)- Proven track record of innovation
in creating novel algorithms and advancing the state of the
artAmazon 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. For individuals with disabilities who
would like to request an accommodation, please visit
https://www.amazon.jobs/en/disability/us.
Keywords: Amazon.com, Bloomfield , Applied Scientist, Other , Newark, New Jersey
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