Applied Scientist
Newark, NJJob$172–223K/yrSeen 1w agoSeen in employer's feed 5 days ago
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At a glance
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Job overview
The Applied Scientist will use scalable machine learning, deep learning, and natural language processing to detect and predict fraud, improve investigations, and develop fraud defenses. The role includes analyzing transaction patterns, building predictive models, and translating findings into actionable risk insights. The scientist will contribute across research, design, and model development, while collaborating with data scientists, engineers, and business teams.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
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 role
In this role, you'll employ scalable 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...
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Protect Audible’s customers and content creators against the onslaught of AI-generated fraud
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Develop Amazon-scale data engineering & modeling pipelines.
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Imagine and invent before the business asks, and create novel fraud detection and mitigation solutions using innovative approaches.
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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.
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Contribute to the growth of the Audible Data Science team by sharing your ideas, intellectual property and learning from others.
ABOUT AUDIBLE
Audible 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
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Experience creating novel algorithms and advancing the state of the art
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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
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Fluent in SQL, Python
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Depth and breadth in novel machine learning technologies
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Machine Learning Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions) or similar cloud-platforms
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Big Data Engineering with Spark/AWS EMR & Glue
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Experience with Agile Software Development
Preferred Qualifications
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Domain knowledge of comparable products (digital, retail)
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Fluency in Java
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Experience in developing and enhancing fraud detection and mitigation models and techniques
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Knowledge of the latest advancements in AI/ML-powered fraud detection
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 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.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits .
USA, NJ, Newark - 172,400.00 - 223,400.00 USD annually
How this job compares
Set against the 1,075 open Applied Scientist jobs on Olive Jobs, counted November 3, 2026.
- Pay
- This posting$172–223K/yr
- US median$158–264K/yr1,036 salary ranges
This range's midpoint, $198K, is close to the US median midpoint ($197K) — in the middle half of Applied Scientist salary ranges across the US.
- Openings
- Olive Jobs lists 10 open Applied Scientist jobs in New Jersey and 1,075 across the US. Under 1% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 5 years of experience; Applied Scientist postings that state a minimum ask for 5 years at the median (918 postings).
- Education
- 582 of the 1,075 open Applied Scientist jobs (54%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 3, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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