Applied Scientist, Private Brands Discovery

Amazon; Vancouver; On-site; CAD 207,000 - 347,000; Full time

Job summary

A leading technology company is seeking a scientist to drive innovative machine learning solutions that enhance customer discovery for its brands. You will be responsible for end-to-end scientific projects, leveraging complex algorithms and data analysis techniques, and presenting analytical insights to leadership. This role requires a collaborative approach with varying teams, and candidates should have a strong background in causal machine learning, programming, and model development, with a PhD or relevant experience.

Benefits

Comprehensive health benefits

Total compensation package including equity

Qualifications

• 3+ years of building models for business applications.
• Experience in patents or publications at top-tier conferences.
• Strong familiarity with algorithms, data structures, and optimization.

Responsibilities

• Drive applied science projects in ML from ideation to launch.
• Present results and insights to technical and business teams.
• Mentor junior scientists and engineers.

Skills

Causal machine learning

Python programming

Machine learning pipelines

Data analysis

Algorithm design

Education

PhD or Master's degree in CS, CE, ML

Tools

Java

C++

Unix/Linux

Job description

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 at Amazon. To 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

• 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

• 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 in patents or publications at top‑tier peer‑reviewed conferences or journals
• 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

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 for this position ranges from $149,300/year up to $249,300/year. Salary is based on a number of factors 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. Applicants should apply via our internal or external career site.