Amazon
Senior Data Scientist, Ring Data Science and Engineering
Amazon, Seattle, Washington, us, 98127
Senior Data Scientist, Ring Data Science and Engineering
Job ID: 2775999 | Amazon.com Services LLCCome build the future of smart security with us. Are you interested in helping shape the future of devices and services designed to keep people close to what’s important?ABOUT RINGWe started in a garage in 2012 when our founder asked a simple question: what if you could answer the front door from your phone? What if you could be there without needing to actually, you know, be there? After many late nights and endless tinkering, our first Video Doorbell was born. That invention has grown into over a decade of groundbreaking products and next-level features. At Ring, we’re committed to helping you be there for what matters.ABOUT THE ROLEThe Senior Data Scientist within Ring Data Science and Engineering plays a pivotal role in shaping how we carry the voice of our customers. We strive to understand their behaviors and preferences to provide them with the best experience connecting with the places, people, and things that matter to them. This role will build scalable solutions and models to support our business functions (Subscriptions, Product, Customer Service). By leveraging statistical analysis and machine learning, you will explain, quantify, predict, and prescribe in support of informing critical business decisions.Key Job Responsibilities
Drive shared understanding among business, engineering, and science teams of domain knowledge of processes, system structures, and business requirements.Apply domain knowledge to identify product roadmap, growth, engagement, and retention opportunities; quantify impact; and inform prioritization.Advocate technical solutions to business stakeholders, engineering teams, and executive level decision makers.Lead development and validation of state-of-the-art technical designs (data pipelines, data models, causal inference, predictive models, data insights/visualizations, etc).Contribute to the hiring and development of others.Communicate strategy, progress, and impact to senior leadership.A Day in the Life
Translate/Interpret complex and interrelated datasets describing customer behavior, messaging, content, product design, and financial impact.Measure/Quantify/Expand: Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.Analyze historical data to identify trends and support decision making.Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.Provide requirements to develop analytic capabilities, platforms, and pipelines.Apply statistical or machine learning knowledge to specific business problems and data.Explore/Enlighten: Formalize assumptions about how users are expected to behave, create statistical definitions of outliers, and develop methods to systematically identify these outliers.Deep dive to explain anomalies and identify fixes.Make decisions and recommendations.Build decision-making models and propose solutions for the defined business problem.Conduct written and verbal presentations to share insights and recommendations to audiences of varying levels of technical sophistication.Utilize code (Python/R/SQL) for data analyzing and modeling algorithms.BASIC QUALIFICATIONS
Bachelor's degree.4+ years of data scientist experience.5+ years of experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, Matlab, etc.).Experience with statistical models (e.g. multinomial logistic regression).5+ years of hands-on experience in modeling and analysis, and in deploying machine learning/deep learning models in production.PREFERRED QUALIFICATIONS
Experience managing data pipelines.Experience as a leader and mentor on a data science team.Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue).Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.Domain knowledge of comparable products and services.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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Job ID: 2775999 | Amazon.com Services LLCCome build the future of smart security with us. Are you interested in helping shape the future of devices and services designed to keep people close to what’s important?ABOUT RINGWe started in a garage in 2012 when our founder asked a simple question: what if you could answer the front door from your phone? What if you could be there without needing to actually, you know, be there? After many late nights and endless tinkering, our first Video Doorbell was born. That invention has grown into over a decade of groundbreaking products and next-level features. At Ring, we’re committed to helping you be there for what matters.ABOUT THE ROLEThe Senior Data Scientist within Ring Data Science and Engineering plays a pivotal role in shaping how we carry the voice of our customers. We strive to understand their behaviors and preferences to provide them with the best experience connecting with the places, people, and things that matter to them. This role will build scalable solutions and models to support our business functions (Subscriptions, Product, Customer Service). By leveraging statistical analysis and machine learning, you will explain, quantify, predict, and prescribe in support of informing critical business decisions.Key Job Responsibilities
Drive shared understanding among business, engineering, and science teams of domain knowledge of processes, system structures, and business requirements.Apply domain knowledge to identify product roadmap, growth, engagement, and retention opportunities; quantify impact; and inform prioritization.Advocate technical solutions to business stakeholders, engineering teams, and executive level decision makers.Lead development and validation of state-of-the-art technical designs (data pipelines, data models, causal inference, predictive models, data insights/visualizations, etc).Contribute to the hiring and development of others.Communicate strategy, progress, and impact to senior leadership.A Day in the Life
Translate/Interpret complex and interrelated datasets describing customer behavior, messaging, content, product design, and financial impact.Measure/Quantify/Expand: Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.Analyze historical data to identify trends and support decision making.Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.Provide requirements to develop analytic capabilities, platforms, and pipelines.Apply statistical or machine learning knowledge to specific business problems and data.Explore/Enlighten: Formalize assumptions about how users are expected to behave, create statistical definitions of outliers, and develop methods to systematically identify these outliers.Deep dive to explain anomalies and identify fixes.Make decisions and recommendations.Build decision-making models and propose solutions for the defined business problem.Conduct written and verbal presentations to share insights and recommendations to audiences of varying levels of technical sophistication.Utilize code (Python/R/SQL) for data analyzing and modeling algorithms.BASIC QUALIFICATIONS
Bachelor's degree.4+ years of data scientist experience.5+ years of experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, Matlab, etc.).Experience with statistical models (e.g. multinomial logistic regression).5+ years of hands-on experience in modeling and analysis, and in deploying machine learning/deep learning models in production.PREFERRED QUALIFICATIONS
Experience managing data pipelines.Experience as a leader and mentor on a data science team.Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue).Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.Domain knowledge of comparable products and services.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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