Data Scientist, Amazon Music - DISCO

About the position

Amazon Music is an immersive audio entertainment service that deepens

connections between fans, artists, and creators. From personalized music

playlists to exclusive podcasts, concert livestreams 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, Consumer Product and Tech (DISCO

CPT) team is looking for a Data Scientist to join a team of Data Scientists,

Analytics Leads, Business Intelligence Engineers and Data Engineers who analyze

big data, provide analytics and insights as well as build models and algorithms

that power product for personalized experiences. The 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, science models, self-service analytics, insights and dashboards,

deliver engagement and retention at scale. In this role, you will pioneer and

execute advanced analytics and experimentation efforts for the Amazon Music

product team. You will work with stakeholders and partners to deliver

experimentation insights, author scientific artifacts, build scalable models to

advance our analytics and science products. The ideal candidate must be willing

to effectively lead science solutions, prioritize across multiple stakeholders

and projects and be ready to jump into a fast-paced, dynamic and fun

environment.

Responsibilities

• Data Scientist II on this role will be a thought partner to Product and

Engineering organizations through their expertise in experimentation,

statistical modeling and advanced analytics

• Conceptualize and drive strategic growth areas: retention, voice + visual

engagement, experimentation, Gen AI initiatives, and product excellence.

• Bridge science, analytics, and engineering to deliver solutions informing

strategic decisions on AM technology investments and long-term business

performance

• Drive experimentation, measurement efficiency tooling, and ROI tracking for AM

leadership

• Build and maintain causal models to understand customer sentiment and its

impact on key engagement/retention metrics

• Develop structural and predictive models using data science workflows to

deliver measurable customer results

• Lead strategic initiatives across visual and voice experiences,

experimentation and customer retention stakeholders

• Conduct experimentation, build causal models to better understand key drivers

for customer retention

• Evaluate existing metrics and lead deep dives to ensure the right measurement

framework is leveraged to measure and enhance user adoption through visual and

voice interfaces

• Partner with product managers to translate business questions into actionable

science projects

• Influence product roadmaps through data-driven insights on customer behavior

patterns

• Identify and resolve customer experience friction points with cross-functional

teams

• Drive adoption of best practices and innovative solutions across the

organization

Requirements

• Bachelor's degree
• 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

• Experience applying theoretical models in an applied environment

Nice-to-haves

• Knowledge of machine learning concepts and their application

to reasoning and problem-solving

• Experience in Python, Perl, or another scripting language
• Experience in defining and creating benchmarks for assessing GenAI model

performance

• Experience applying quantitative analysis to solve business problems and

making data-driven business decisions

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life &

AD&D insurance and option for Supplemental life plans, EAP, Mental Health

Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy

Reimbursement coverage)

• 401(k) matching
• paid time off
• parental leave