Amazon
Data Scientist, Amazon Music DISCO
Amazon, Sunnyvale, California, United States, 94087
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 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. Learn more at https://www.amazon.com/music.
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, Business Intelligence Engineers and Data Engineers who analyze big data, provide analytics and insights as well as build models and algorithms that power the Music product experiences. DISCO CPT 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. In this role, you will set the science vision and direction for the team and collaborate with internal stakeholders across marketing, growth, product, science and finance teams to scale and advance our science offerings. The ideal candidate must be willing to effectively lead large scale science solutions, prioritize across multiple stakeholders and projects and be ready to jump into a fast-paced, dynamic and fun environment.
Key job responsibilities
Predictive Modeling:
Develop predictive models to identify potentially fraudulent streaming activities, or content uploads. Utilize anomaly detection techniques to surface suspicious patterns in user behavior, and content metadata
Collaborate with the FCRM team to refine fraud detection models and improve the accuracy of fraud identification in addition to improving streaming fraud entitlement estimation by using ML output to identify outliers
Develop models to automate metadata enrichment and quality assurance processes
Develop models to determine drivers of key performance metrics like MAU and HPC and automate the process of deep diving into variances in these metrics
Experimentation and A/B Testing:
Collaborate with product and engineering teams to design rigorous experiments to evaluate the impact of new features or algorithms (e.g., the Playlist Song Recommendation experiments).
Analyze the results of these experiments, identify learning, and provide recommendations to optimize the solutions
Partner with Sr. Data Scientists to analyze and propose key experimentation success and guardrail metrics for business like AMOR, Catalog quality etc.
Deep dives and analysis:
Develop metrics and rules that help identify metadata tag defects and improve metadata quality and enable more precise Catalog tiering
Analyze the current state of metadata, including genre coverage, artist disambiguation, and track-level information and propose strategies to improve the overall metadata quality and coverage across the catalog
Determine relationship between metadata quality improvements and customer engagement to guide prioritization of ingestion and coverage
Cross - Functional Collaboration:
Partner with product, catalog, and engineering teams to understand business challenges and translate them into analytical science initiatives
Evangelize the use of experimentation and advanced analytics science across the organization
Mentor and train other analysts and data scientists to build their skills
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
Experience applying theoretical models in an applied environment
Preferred Qualifications
Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company
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.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500/year in our lowest geographic market up to $212,800/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.
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. Learn more at https://www.amazon.com/music.
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, Business Intelligence Engineers and Data Engineers who analyze big data, provide analytics and insights as well as build models and algorithms that power the Music product experiences. DISCO CPT 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. In this role, you will set the science vision and direction for the team and collaborate with internal stakeholders across marketing, growth, product, science and finance teams to scale and advance our science offerings. The ideal candidate must be willing to effectively lead large scale science solutions, prioritize across multiple stakeholders and projects and be ready to jump into a fast-paced, dynamic and fun environment.
Key job responsibilities
Predictive Modeling:
Develop predictive models to identify potentially fraudulent streaming activities, or content uploads. Utilize anomaly detection techniques to surface suspicious patterns in user behavior, and content metadata
Collaborate with the FCRM team to refine fraud detection models and improve the accuracy of fraud identification in addition to improving streaming fraud entitlement estimation by using ML output to identify outliers
Develop models to automate metadata enrichment and quality assurance processes
Develop models to determine drivers of key performance metrics like MAU and HPC and automate the process of deep diving into variances in these metrics
Experimentation and A/B Testing:
Collaborate with product and engineering teams to design rigorous experiments to evaluate the impact of new features or algorithms (e.g., the Playlist Song Recommendation experiments).
Analyze the results of these experiments, identify learning, and provide recommendations to optimize the solutions
Partner with Sr. Data Scientists to analyze and propose key experimentation success and guardrail metrics for business like AMOR, Catalog quality etc.
Deep dives and analysis:
Develop metrics and rules that help identify metadata tag defects and improve metadata quality and enable more precise Catalog tiering
Analyze the current state of metadata, including genre coverage, artist disambiguation, and track-level information and propose strategies to improve the overall metadata quality and coverage across the catalog
Determine relationship between metadata quality improvements and customer engagement to guide prioritization of ingestion and coverage
Cross - Functional Collaboration:
Partner with product, catalog, and engineering teams to understand business challenges and translate them into analytical science initiatives
Evangelize the use of experimentation and advanced analytics science across the organization
Mentor and train other analysts and data scientists to build their skills
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
Experience applying theoretical models in an applied environment
Preferred Qualifications
Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company
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.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500/year in our lowest geographic market up to $212,800/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.