Data Scientist, Amazon Music - DISCO

Description

Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert live streams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service:
Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale.

The Data, Insights, Science and Optimization, Music Product and Tech (DISCO MPT) team is looking for a Data Scientist to join a team of scientists and engineers who analyze big data, provide analytics and insights and build models and algorithms to power Music product experiences. In this role, you will set the science vision and direction for the team and collaborate with internal stakeholders across product, science and finance to scale and advance our science offerings.

You will lead large scale science solutions, prioritize across multiple stakeholders and projects and be part of a fast-paced, dynamic and fun environment.

Key job responsibilities

* Lead the research and development of models and science products powering personalized recommendations

* Partner with product leaders at Amazon Music to develop science-driven business strategies

* Partner with science, marketing and product teams across Amazon Entertainment and subscription businesses

* Educate internal teams on analytics, insights and measurement

* Develop models to determine drivers of key performance metrics, and automate the process of deep diving into variances

* Collaborate with product and engineering teams to evaluate the impact of new features or algorithms (e.g., the Playlist Song Recommendation experiments)

* Analyze the results of experiments and provide recommendations to optimize solutions

* Partner with Senior Data Scientists and Product Managers to analyze and propose success and guardrail metrics

* Encourage the use of experimentation and advanced analytics across the organization

About the team

The DISCO team focuses on accelerating Amazon Music customer growth by empowering product teams to make sound, customer-centric decisions through data and insights. We build data pipelines, self-service analytics, insights and predictive models enabling acquisition, engagement and retention at scale with personalized customer touchpoints.

Basic Qualifications

* 2+ years of data scientist experience

* 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience

* 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience

* 1+ years of guiding and coaching a group of researchers experience

* 1+ years of working with or evaluating AI systems experience

* 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience

* Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

* Experience applying theoretical models in an applied environment

Preferred Qualifications

* Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)

* Knowledge of machine learning concepts and their application to reasoning and problem-solving

* Experience in Python, Perl, or another scripting language

* Experience in a ML or data scientist role with a large technology company

* Experience in defining and creating benchmarks for assessing GenAI model performance

* Experience working on multi-team, cross-disciplinary projects

* Experience applying quantitative analysis to…