Manager, Applied Science
Finance & Growth | Job ID 3041510Job Summary
At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us.
ABOUT THIS ROLE
As an Applied Science Manager, you will lead of a team of scientists to solve complex real-world problems at scale, draw inspiration from the latest science and technology to empower undefined/untapped business use cases, delve into customer requirements, collaborate with tech and product teams on design, and create production-ready models that span various domains, including machine learning, causal inference, artificial intelligence (AI), natural language processing (NLP), reinforcement learning (RL), real-time and distributed systems. Your primary focus will be on designing, developing, and deploying highly innovative modeling techniques to production to advance the state of the art in aforementioned domains. Your decision-making will consistently incorporate robust, data-driven business and technical judgment. You will drive discussions with engineering, product, and marketing partners, and have the technical depth to give guidance to data/research/applied scientists and software developers to test and build scalable customer-facing experiences. You will have the opportunity to innovate, invent, think big, and streamline cutting-edge optimization services and algorithms to influence the experiences of millions of customers.
As an Applied Science Manager, you will...
- Understand large complex use cases across the business and design scalable, efficient, automated model solutions
- Coordinate a team of scientists in a matrixed environment with engineering & product partners to deliver these solutions
- Drive and lead strategic initiatives to employ the most recent advances in ML/AI in a fast-paced, experimental environment
- Mentor and grow scientists in your team and across Audible
ABOUT AUDIBLE
Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.
ABOUT THIS ROLE
As an Applied Science Manager, you will lead of a team of scientists to solve complex real-world problems at scale, draw inspiration from the latest science and technology to empower undefined/untapped business use cases, delve into customer requirements, collaborate with tech and product teams on design, and create production-ready models that span various domains, including machine learning, causal inference, artificial intelligence (AI), natural language processing (NLP), reinforcement learning (RL), real-time and distributed systems. Your primary focus will be on designing, developing, and deploying highly innovative modeling techniques to production to advance the state of the art in aforementioned domains. Your decision-making will consistently incorporate robust, data-driven business and technical judgment. You will drive discussions with engineering, product, and marketing partners, and have the technical depth to give guidance to data/research/applied scientists and software developers to test and build scalable customer-facing experiences. You will have the opportunity to innovate, invent, think big, and streamline cutting-edge optimization services and algorithms to influence the experiences of millions of customers.
As an Applied Science Manager, you will...
- Understand large complex use cases across the business and design scalable, efficient, automated model solutions
- Coordinate a team of scientists in a matrixed environment with engineering & product partners to deliver these solutions
- Drive and lead strategic initiatives to employ the most recent advances in ML/AI in a fast-paced, experimental environment
- Mentor and grow scientists in your team and across Audible
ABOUT AUDIBLE
Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.
Basic Qualifications
- Masters degree in a quantitative field (economics, computer science, statistics, or equivalent)
- 5+ years of experience as a scientist / science manager applying ML to solve complex problems for large-scale applications
- 2+ years of experience as a science manager with a successful record of developing junior members to a successful career track
- Fluent in SQL, Python
- Experience using professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Deep technical experience in cloud-based distributed software design and development, ML Pipeline orchestration, especially utilizing AWS services
- Big Data Engineering with Spark / AWS EMR & Glue
- Experience with Agile Software Development
- 5+ years of experience as a scientist / science manager applying ML to solve complex problems for large-scale applications
- 2+ years of experience as a science manager with a successful record of developing junior members to a successful career track
- Fluent in SQL, Python
- Experience using professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Deep technical experience in cloud-based distributed software design and development, ML Pipeline orchestration, especially utilizing AWS services
- Big Data Engineering with Spark / AWS EMR & Glue
- Experience with Agile Software Development
Preferred Qualifications
- PhD in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field; or equivalent combination of technical education and work experience
- Excellent written and verbal communication skills with the ability to present complex technical information in a clear and concise manner to a variety of audiences
- Domain knowledge of comparable products (digital, retail)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $165,500/year in our lowest geographic market up to $286,000/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.
- Excellent written and verbal communication skills with the ability to present complex technical information in a clear and concise manner to a variety of audiences
- Domain knowledge of comparable products (digital, retail)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $165,500/year in our lowest geographic market up to $286,000/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.
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