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Description

Amazon’s Customer Behavior Analytics org is looking for an Principal Data Scientist to spearhead the rapid growth of our Marketing Measurement solutions. The team focuses on building scalable ML and causal inference solutions to estimate the effectiveness of Amazon marketing efforts and provide actionable insights to the various marketing teams within Amazon. This is a high-impact role with opportunities to directly influence billions of dollars in investments across worldwide marketplaces, and inform marketing and marketplace leaders on where to invest, how much to invest and why. We work closely with business stakeholders and strive to continuously produce tangible impact on the company’s strategic and tactical planning and operations.

A successful candidate will be a self-starter, comfortable with ambiguity, able to think big and be creative, while still paying careful attention to detail. You should be able to translate how data represents the customer journey, be comfortable dealing with large and complex data sets, and have experience using machine/deep learning at scale to solve business problems. You should have strong analytical and communication skills, be able to work with product managers and software teams to define key business questions and work with the analytics team to solve them. You will apply your expertise in data science, and statistics, to identify opportunities for further research and to provide insights that drive larger initiatives. You will join a highly collaborative and diverse working environment that will empower you to shape the future of Amazon marketing, as well allow you to be part of the large science community within the Customer Behavior Analytics (CBA) organization.

Key job responsibilities

Technical Leadership:

- Architecting complex data science solutions focusing on customer behavior patterns

- Leading advanced analytics projects from conception to deployment

- Developing and implementing sophisticated machine learning models for customer segmentation, lifetime value prediction, and churn analysis

- Establishing best practices for data science methodologies within the team

Strategic Impact:

- Translating business problems into analytical frameworks

- Identifying opportunities for data-driven innovation in customer experience

- Providing strategic recommendations to senior management based on analytical insights

- Defining KPIs and metrics to measure customer behavior and engagement

Team Leadership:

- Mentoring junior scientists and engineers

- Setting technical direction for the team

- Collaborating with cross-functional teams (Marketing, Product, Engineering)

- Leading code reviews and ensuring quality standards

Advanced Analytics:

- Creating recommendation systems and personalization algorithms

- Performing advanced statistical analysis

- Building real-time analytics solutions for customer insights

Business Communication:

- Presenting complex findings to non-technical stakeholders

- Creating executive-level reports and dashboards

- Collaborating with product teams to implement data-driven features

Technical Stack Management:

- Evaluating and implementing new tools and technologies

- Ensuring scalability of data science solutions

About the team

The Customer Behavior Analytics (CBA) organization owns Amazon’s insights pipeline, from data collection to deep analytics. We aspire to be the place where Amazon teams come for answers, a trusted source for data and insights that empower our systems and business leaders to make better decisions. Our outputs shape Amazon product and marketing teams’ decisions and thus how Amazon customers see, use, and value their experience.

Basic Qualifications

- 10+ years of non-internship professional data science and simulation experience in a system engineering domain.

- Masters degree in relevant discipline, engineering or science.

- Hands on experience articulating model trade-offs and results analysis to business partners.

- Hands on experience with R, Python, Jupyter and other data science and simulation tools, languages and technology.

- Experience applying theoretical models in an applied environment

Preferred Qualifications

- Ph.D. in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a closely related field.

- Proven track record of delivering as part of cross-disciplinary teams.

- Strong communication and presentation skills.

- Comfortable working in a fast paced, highly collaborative, dynamic work environment.

- Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $145,800/year in our lowest geographic market up to $294,700/year in our highest geographic market. Pay is based on a number of factors including market location 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. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.