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Open nowPosted yesterday

Sr. Applied Scientist, Agent Evaluation and Experimentation, DTx Science

Amazon / AWS23,007 open roles

Where
New York, New York, United States
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Your applicationOpen nowSr. Applied Scientist, Agent Evaluation and Experimentation, DTx ScienceAmazon / AWS · New York, New York, United States

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The clock on this job

Early applications get read.

8.2% of postings close within 7 days. Measured by our own scanner across the market. Amazon / AWS postings stay open a median of 8 days.

Share of postings closed within
  1. 1.8%1 day
  2. 3.6%3 days
  3. 8.2%7 days
  4. 15.2%14 days
  5. 34.0%30 days
This job: posted yesterday

Amazon / AWS median: 8 days open

The posting

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

Demand Tech Experience (DTx), as an org, owns the Amazon Ads Console — the advertiser-facing workspace for creating and managing campaigns, reviewing performance, and acting on recommendations used by millions of advertisers. Our team, DTx Science, is the centralized science team within DTx, dedicated to improving and protecting the advertiser experience across ad consoles through applied science methodologies. The team drives impact through four core functions: Ad Console Personalization, Recommendation Development, Ad Console Experimentation, and DVA Agent Evaluation and Impact Measurement.

In this role, you will work closely with business leaders, stakeholders, and cross-functional teams to drive program success through ML- and agentic-driven solutions. You will shape the applied science roadmap, promote a culture of data-driven decision-making, and deliver significant business impact for millions of advertisers worldwide and the company using advanced data techniques and applied science methodologies.

Key job responsibilities As an Sr. Applied Scientist on this team, you will - Lead the development of agent evaluation, agent impact measurement, agent experimentation, and agent advertiser experience - Lead high-ambiguity projects and drive alignment across teams on science and engineering solutions. - Drive adoption of state-of-the-art scientific technologies in generative AI, reinforcement learning, causal inference, classical machine learning, and natural language processing to improve the team's existing science solutions. - Translate complex scientific challenges into clear and impactful solutions for business stakeholders. - Mentor and guide junior scientists, fostering a collaborative and high-performing team culture. - Foster collaborations between scientists to move faster, with broader impact. - Regularly engage with the broader scientific community with presentations, publications, and patents.

About the team The DTx Science team is the centralized science team within Demand Tech Experience (DTx), dedicated to improving and protecting the advertiser experience across ad consoles through applied science methodologies. The team drives impact through four core functions: Ad Console Personalization, Recommendation Development, Ad Console Experimentation, and DVA Agent Evaluation and Impact Measurement.

Improve advertiser experience: Ad Console Personalization and Recommendation Development aim to improve the advertiser ad console experience by providing customized and personalized console experiences for each user and increasing their ad performance with relevant, science-backed onboarding and oppertunty recommendations.

Protect advertiser experience: Ad Console Experimentation and DVA Agent Evaluation and Impact Measurement protect the advertiser experience by supporting the organization in making data-driven decisions to launch UX and agentic features that benefit advertisers.

- 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

- 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.

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 USA, WA, SEATTLE - 167,100.00 - 226,100.00 USD annually

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