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

About the role

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.

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.

Additional information

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Pay and benefits

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.

• USA, CA, Palo Alto - 192,200.00 - 260,000.00 USD annually
• USA, NY, New York - 183,800.00 - 248,700.00 USD annually
• USA, WA, SEATTLE - 167,100.00 - 226,100.00 USD annually