Key job responsibilities
We are seeking an Applied Scientist who has a solid background in applied Machine Learning and Data Science, deep passion for building data-driven products, ability to formulate data insights and scientific vision, and has a proven track record of executing complex projects and delivering business impact. Specific responsibilities include:
• Data driven insights to accelerate acquisition of new members.
• Grow benefits adoption based on customer segment, vertical, and drive customers to their "aha moment".
• Work closely with software engineering teams to drive model implementations and new feature creations.
• Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
• Advance team's engineering craftsmanship and drive continued scientific innovation as a thought leader and practitioner.
About the team
The Marketing Science team applies scientific methods and research techniques to enhance our understanding of AB consumer behavior, market trends, and the effectiveness of marketing strategies. Our goal is to develop and advance theories and models that can be used to make informed decisions in marketing and to provide insights into consumer decision-making processes. Additionally, we seek to identify and explore emerging trends and technologies in marketing, and to develop innovative approaches for addressing the challenges and opportunities in the field.
BASIC QUALIFICATIONS
- Experience programming in Java, C++, Python or related language
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Experience building machine learning models or developing algorithms for business application
PREFERRED QUALIFICATIONS
- Experience implementing algorithms using both toolkits and self-developed code
- Have publications at top-tier peer-reviewed conferences or journals
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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 $129,400/year in our lowest geographic market up to $212,800/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.