Applied Scientist, Amazon Ads, Forecasting, Insights and Guidance (FIG)

Amazon Inc.; Palo Alto (CA); Presencial; USD 172 000 - 222 000; Tempo integral

Resumo da oferta

Amazon is seeking an Applied Scientist for Ads forecasting to advance our FIG platform. You will move models from problem formulation to production, collaborating with engineers and product teams to deliver measurable advertiser impact.

You will train and refine ML models, design experiments, and perform statistical analyses to validate real-world results, while exploring new techniques to improve forecasting and guidance for advertisers.

Qualificações

• 3+ years of building models for business application experience.
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience.
• Experience programming in Java, C++, Python or related language.
• Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.

Responsabilidades

• Lead end-to-end ML initiatives with high ambiguity, scale, and complexity, from problem framing through production deployment.
• Develop models that improve advertiser outcomes on Amazon's advertising platform.
• Design and execute experiments and statistical analyses to validate real-world impact.
• Partner with engineering and product to ship science into customer-facing products responsibly.
• Advance the state of the art by researching new techniques and applying them to advertising problems.

Conhecimentos

Java

C++

Python

Formação académica

PhD

Master's degree

Ferramentas

PyTorch

Descrição da oferta de emprego

Applied Scientist, Amazon Ads, Forecasting, Insights and Guidance (FIG)

Job ID: 10555006 | Amazon.com Services LLC

Help build Amazon's world-class advertising business by applying machine learning and generative AI to hard problems in campaign optimization. As an Applied Scientist, you'll take models from problem formulation to production, working closely with engineering and product partners to deliver measurable advertiser impact.

• Experience training or adapting large language models
• Experience with sequential decision-making or optimization under uncertainty
• Experience with causal inference or rigorous evaluation of ML systems
• Experience designing experiments and performing statistical analysis of results
• Experience with modern deep learning frameworks such as PyTorch

Key job responsibilities

• Lead end-to-end ML initiatives with high ambiguity, scale, and complexity, from problem framing through production deployment
• Develop models that improve advertiser outcomes on Amazon's advertising platform
• Design and execute experiments and statistical analyses to validate real-world impact
• Partner with engineering and product to ship science into customer-facing products responsibly
• Advance the state of the art by researching new techniques and applying them to advertising problems

About the team

You’ll join a highly motivated, collaborative, and entrepreneurial team with a broad mandate to experiment, innovate, and break new ground. Your work will directly influence advertiser success and shape the future of Amazon Advertising.

Basic Qualifications

• 3+ years of building models for business application experience
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• Experience programming in Java, C++, Python or related language
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Preferred Qualifications

• Experience building machine learning models or developing algorithms for business application
• Experience in designing experiments and statistical analysis of results

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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, CA, Palo Alto - 171,600.00 - 222,200.00 USD annually