Sr. Applied Scientist, Amazon Business Ads

13 ore fa


Como, Italia Amazon A tempo pieno

Sr. Applied Scientist, Amazon Business Ads Job ID: 3129612 | 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 areas Earn 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. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site. Posted: December 23, 2025 (Updated 1 day ago) #J-18808-Ljbffr



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