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Sr. Applied Scientist, Amazon Business Ads
Job ID: 3177499 | Amazon.com Services LLC
Advertising at Amazon is growing incredibly fast and we are responsible for defining and delivering a collection of advertising products that drive discovery and sales.
Amazon Business Ads is equally growing fast ($XXXMs to $XBs) and owns engineering and science for the AB WW ad experience. We build business-to-business ("B2B") specific ad solutions distributed across retail and ad systems for shopper and advertiser experiences. Some include new ad placements or widgets, creatives, sourcing techniques, ad campaign management capabilities and much more! We consider unique AB qualities which are differentiated from the consumer experience such as varying shopper role types, purchasing complexities based on business size and industry (eg education vs healthcare), AB specific features (eg business discounts, buying policies to restrict and prefer products), and AB buyer behaviors (eg buying in bulk).
We are seeking a scientific leader who can drive innovation in complex problem areas and new business initiatives. The ideal candidate will:
Technical & Research Requirements
Demonstrate fluency in Python, R, Matlab or other statistical languages and familiarity with deep learning frameworks like PyTorch, TensorFlow
Lead end-to-end solution development from research to prototyping and experimentation
Write and deploy significant parts of scientifically novel software solutions into production
Leadership & Influence
Drive team's scientific agenda by proposing new initiatives and securing management buy-in including PM, SDM
Mentor colleagues and contribute to their professional development
Build consensus on large projects and influence decisions across different teams in Ads
Key Leadership Principles
Dive Deep: Uncover non-obvious insights in data
Deliver Results: Create solutions aligned with customer and product needs
Learn and Be Curious: Demonstrate self-driven desire to explore new research areasEarn Trust: Build relationships with stakeholders through understanding business needs
Basic Qualifications
3+ years of building machine learning models for business application experience
PhD, or Master's degree and 6+ years of applied research experience
Experience programming in Java, C++, Python or related language
Experience with neural deep learning methods and machine learning
Preferred Qualifications
Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
Experience with large scale distributed systems such as Hadoop, Spark etc.
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.
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, NY, New York – 183,800.00 – 248,700.00 USD annually
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Dettagli Lavoro
Data Pubblicazione:
February 28, 2026
Tipo di Lavoro:
Gestione e operazioni
Località:
Italy
Azienda:
Vendita al dettaglio e all'ingrosso / Import-export
Pronto a Candidarti?
Non perdere questa opportunità! Candidati ora e unisciti al nostro team.