Amazon
Data Scientist II, Amazon Music Catalog
Amazon, Seattle, Washington, us, 98127
Job ID: 2798053 | Amazon.com Services LLCAmazon 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.
Read on to fully understand what this job requires in terms of skills and experience If you are a good match, make an application.
Amazon Music Catalog team is seeking a skilled and eager Data Scientist who will join a team of experts in the field of machine learning and work together to break new ground in the understanding of various forms of music assets while building useful applications that impact millions of end users’ experience of listening to music. We work on various problems of data analytics, machine learning, signal processing, deep learning, LLMs and NLP, Fraud analytics and safety. You'll work in a collaborative environment where you can pursue applied research, with many peta-bytes of data, work on problems that haven’t been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research. You'll see the work you do directly improve the experience of Amazon Music customers on Alexa/Echo, mobile, and web.
Key job responsibilities
Use machine learning, deep learning, LLMs and NLP techniques to create scalable solutions for business problemsAnalyze and extract relevant information from large amounts of Amazon's data to help automate and optimize key processesDesign, development and evaluation of highly innovative models for predictive learningWork closely with software engineering teams to drive model implementations and new feature creationsEstablish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementationResearch and implement novel machine learning and statistical approachesBuild data engineering pipelines to help software developer teams to design and deploy features.
About the teamOur team is dynamic group of highly qualified scientists and engineers building the technology stack for the Amazon Music Catalog team. We work closely with product teams to deliver high value and high impact solutions that affect multiple other downstream teams like Search, Personalization, Recommendation, CRM and others. We build solutions to real world problems at scale with speed, performance and deliver solutions quick to meet the demands of customers. Everyone on our team has a meaningful impact on product features, new directions in music streaming, and customer engagement.
BASIC QUALIFICATIONS - Bachelor's degree- Master's degree- 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- 2+ years of data scientist 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- Experience programming in Java, C++, Python or related languagePREFERRED QUALIFICATIONS - PhD- Experience in Python, Perl, or another scripting language- Experience in a ML or data scientist role with a large technology company- Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.- Knowledge of LLMs, NLP and graph ML techniques is highly valued.
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.
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Read on to fully understand what this job requires in terms of skills and experience If you are a good match, make an application.
Amazon Music Catalog team is seeking a skilled and eager Data Scientist who will join a team of experts in the field of machine learning and work together to break new ground in the understanding of various forms of music assets while building useful applications that impact millions of end users’ experience of listening to music. We work on various problems of data analytics, machine learning, signal processing, deep learning, LLMs and NLP, Fraud analytics and safety. You'll work in a collaborative environment where you can pursue applied research, with many peta-bytes of data, work on problems that haven’t been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research. You'll see the work you do directly improve the experience of Amazon Music customers on Alexa/Echo, mobile, and web.
Key job responsibilities
Use machine learning, deep learning, LLMs and NLP techniques to create scalable solutions for business problemsAnalyze and extract relevant information from large amounts of Amazon's data to help automate and optimize key processesDesign, development and evaluation of highly innovative models for predictive learningWork closely with software engineering teams to drive model implementations and new feature creationsEstablish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementationResearch and implement novel machine learning and statistical approachesBuild data engineering pipelines to help software developer teams to design and deploy features.
About the teamOur team is dynamic group of highly qualified scientists and engineers building the technology stack for the Amazon Music Catalog team. We work closely with product teams to deliver high value and high impact solutions that affect multiple other downstream teams like Search, Personalization, Recommendation, CRM and others. We build solutions to real world problems at scale with speed, performance and deliver solutions quick to meet the demands of customers. Everyone on our team has a meaningful impact on product features, new directions in music streaming, and customer engagement.
BASIC QUALIFICATIONS - Bachelor's degree- Master's degree- 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- 2+ years of data scientist 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- Experience programming in Java, C++, Python or related languagePREFERRED QUALIFICATIONS - PhD- Experience in Python, Perl, or another scripting language- Experience in a ML or data scientist role with a large technology company- Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.- Knowledge of LLMs, NLP and graph ML techniques is highly valued.
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.
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