Sr. Data Scientist, Everyday Essentials Brand Health

Sr. Data Scientist, Everyday Essentials Brand Health Job ID: 2920386 | Amazon.com Services LLC Are you passionate about working with Amazon-scale data, deep analytics, and data science? Do you thrive on developing innovative models and insights that elevate customer shopping experience while ensuring brand integrity and product accuracy? If so, join our team and play a pivotal role in shaping the future of Amazon's Consumables shopping experience! We are looking for an experienced and self-driven Senior Data Scientist to help us leverage Amazon-scale data to improve the accuracy, integrity, and presentation of Consumables everyday essentials. In this role, you will further the development and application of modeling and analytics methods to examine the complex data flows of customer shopping data and brand catalogs, to generate actionable insights for a wide breadth of product teams. You will lead the development, improvement, and expansion of Amazon's systems and mechanisms for protecting and ensuring the accuracy of our everyday essentials product offerings. You will make high judgment decisions, present persuasive data cases to executive leadership, and have an enduring impact on the future of Amazon's Consumables online shopping experience. You will work closely with a high-energy team consisting of data science, data engineering, business intelligence engineering, and product management tech, as well as cross-functionally across many partner teams. You will lead your teammates and partner teams through high complexity with data modeling to arrive at clear strategic direction. The tools you build will have visibility at the highest levels of Amazon's leadership team. Key job responsibilities Oversee multiple model development programs in various stages of the lifecycle, from conception to development, to launch, expansion, and retirement. Lead and direct engineering of massive datasets, effective exploratory data analysis, and model building using industry standard AI/ML models. Define creative, high-quality, long-term product roadmaps based on team strategy and vision. Partner with engineering teams to define data logging requirements and getting these prioritized in engineering roadmaps. Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers. Innovate by adapting new modeling techniques and procedures. Manage prioritization and trade-offs among customer experience, performance, and operational support load. Design A/B tests and conduct statistical analysis on their results. Mentor junior engineers and scientists. Research and implement ML and statistical approaches to add value to the business. A day in the life As a Senior Data Scientist in the Everyday Essential Brand Health (EEBH) team, your day will be dynamic and impactful. Your day might start with a review of current priorities which were aligned with your PM-T partners. Your morning could involve diving into an experiment's results, analyzing the impact of a mechanism on product discoverability. Midday, you might collaborate with PM-Ts to review the result of a detection model and provide data-driven recommendations to optimize outputs. In the afternoon, you could be partnering with BIEs to enhance data pipelines, or presenting insights to leadership to drive strategic decisions. Throughout the day, you'll be leveraging the latest data science techniques to solve complex problems, ensuring Amazon customers receive an accurate and trustworthy shopping experience for everyday essentials. About the team The Everyday Essential Brand Health (EEBH) team is dedicated to earning the trust of both customers and brand owners by ensuring the accurate and high-quality presentation of Consumables everyday essentials on Amazon. Our mission is to protect top brands, maintain product integrity, and enhance the shopping experience by leveraging data-driven insights and scalable solutions. We work at the intersection of data science, engineering, and product management to develop mechanisms that safeguard brand representation and ensure customers can confidently discover and purchase essential products with trust and ease. BASIC QUALIFICATIONS 6+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience. Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science. 6+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience. Experience with machine learning and emerging modeling methods. PREFERRED QUALIFICATIONS Experience managing data pipelines. Experience as a leader and mentor on a data science team. 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 this link for more information. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/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 this link . #J-18808-Ljbffr

Created: 2025-03-10