Applied Scientist, Private Brands

Position: Applied Scientist, Amazon Private Brands
Description

The Private Brands Discovery team designs innovative machine learning solutions to drive customer awareness for Amazon's own brands and help customers discover products they love. Private Brands Discovery is an interdisciplinary team of Scientists and Engineers, who incubate and build disruptive solutions using cutting-edge technology to solve some of the toughest science problems  this end, the team employs methods from Natural Language Processing, Deep learning, multi-armed bandits and reinforcement learning, Bayesian Optimization, causal and statistical inference, and econometrics to drive discovery across the customer journey.

Our solutions are crucial for the success of Amazon's own brands and serve as a beacon for discovery solutions across Amazon.

This is a high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and engineers. As a scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms.

Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.. With a focus on bias for action, this individual will be able to work equally well with Science, Engineering, Economics and business teams.

Key job responsibilities

Key job responsibilities

- Experience in causal ML and treatment effect estimation, including methods like propensity scoring, doubly robust estimators, and uplift modeling.

- Strong background in Python, ML pipelines, and deploying models to production with robust monitoring and evaluation.

- Familiarity with causal inference frameworks and translating business questions into actionable causal insights.

- Drive applied science projects in machine learning end-to-end: from ideation over prototyping to launch. For example, starting from deep scientific thinking about new ways to support customers' journeys through discovery, you analyze how customers discover, review and purchase Private Brands to innovate marketing and merchandising strategies.

- Propose viable ideas to advance models and algorithms, with supporting argument, experiment, and eventually preliminary results.

- Invent ways to overcome technical limitations and enable new forms of analyses to drive key technical and business decisions.

- Present results, reports, and data insights to both technical and business leadership.

- Constructively critique peer research and mentor junior scientists and engineers.

- Innovate and contribute to Amazon's science community and external research communities.

Basic Qualifications

- 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 using Unix/Linux

- Experience in professional software development

- Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices.

- Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences.

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  (Use the "Apply for this Job" box below).  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   .

USA, WA, Seattle -  -  USD annually