Senior Data Scientist, Books Personalization Experience – USA, WA, Seattle

Amazon

  • Full Time

DESCRIPTION

Passionate about books? The Amazon Books personalization team is looking for a books obsessed Senior Data Scientist help invent, design, and deliver cutting-edge science solutions to make it easier for millions of customers to find the next book they will love.
In this role you will:

– Be a part of a growing and vibrant team of scientists, economists, engineers, analysts, and business partners.
– Use Amazon’s large-scale computing and data resources to generate deep understandings of our customers, and products.
– Build scalable solutions and models to support Books Personalization & Recommendations space.
– Leverage a range of methods including machine learning, statistics, analytics & insights to improve the experience for millions of customers.
– Translate business goals into agile, insightful analytics. Seek to create value for both stakeholders and customers, and present findings in a clear, actionable way to managers and senior leaders.

Key job responsibilities
As a Senior Data Scientist, you will:

– Collaborate with AI/ML scientists and engineers to to research, design, develop, and evaluate cutting-edge ML algorithms & insights to address real-world challenges.
– Own science artifacts that improve the recommendations experience for customers.
– Imagine, invent, and proactively deliver applications using cutting-edge approaches.
– Make sense of a wall of data by developing compelling data visualizations, creating hypothesises, and driving experimentation and innovation across the team.

A day in the life
From day-to-day, you will research, develop insights, support development of models that power customer facing recommendations, design and implement A/B test experiments, as well as collaborate with engineers, product, and other scientists to get machine learning solutions into production.

About the team
We are Books Personalization Experience team, a collaborative group of Scientists, ML Engineers, Product Managers, and multiple engineering teams that aims to help find the right next read for customers through high quality personalized book recommendation experiences. Books Personalization Experience is a part of the Books Content Demand organization, which focuses on surfacing the best books for customers wherever they are in their current book journey.

BASIC QUALIFICATIONS

– 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
– 4+ years of data scientist experience
– Experience with statistical models e.g. multinomial logistic regression

PREFERRED QUALIFICATIONS

– 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
– 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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

 

USA, WA, Seattle