Sr. Applied Scientist, Worldwide Installments Science \u0026 Engineering
Seattle, Washington
Amazon Worldwide Installments is one of the fastest growing businesses within Amazon. We are Consumer FinTech embedded within Amazon and we are looking for an Applied Scientist to join the team. This group has been entrusted with a massive charter that will impact every customer that visits Amazon.com. We are building the next generation of features and payment products that maximize customer enablement in a simple, transparent, and customer obsessed way. Through these products, we will deliver value directly to Amazon customers improving the shopping experience for hundreds of millions of customers worldwide. Our mission is to delight our customers by building payment experiences and financial services that are trusted, valued, and easy to use from anywhere in any way.
As an Applied Scientist within Worldwide Installments, you will be responsible for building machine learning models and pipelines with direct customer impact. These models represent a core capability for Worldwide Installments and businesses across Amazon. Your work will directly impact customers by influencing how they interact with financing options to make purchases. You will work across functions including data engineering, software development, and business to induce data driven decisions at every level of the organization.
Key job responsibilities
This role will be responsible for:
• \tDeveloping production machine learning models and pipelines for the WW Installments Competitive Pricing team that directly impact customers.
• \tApply expertise in machine learning to develop large-scale production systems that are deployed across Amazon businesses.
• \tIdentify business opportunities, define and execute modeling approach, then deliver outcomes to various Amazon businesses with an Amazon-wide perspective for solutions.
• \tLead the implementation of production ML from a scientific perspective including identifying potential risks, key milestones, and paths to mitigate risks.
• \tIdentifying new opportunities to influence business strategy and product vision using data science and machine learning.
• \tContinually improve the WW Installments ML roadmap automating and simplifying whenever possible.
• \tCoordinate support across engineers, scientists, and stakeholders to deliver ML pipelines, analytics projects, and build proof of concept applications.
• \tWork through significant business and technical ambiguity delivering on analytics roadmap across the team with autonomy.
A day in the life
We directly solve customer problems and our output has direct customer impact. As a result, we're always working on a novel customer problem that has never been researched let alone solved. You might start a day developing a model that will be surfaced on Amazon. From there, you will join a design review and provide feedback to more jr scientists. This is followed by a business review of your model with high ranking stakeholders (Director/VP). Finally, day will end consulting with a partner that will use one of our models to deliver brand new products or experiences for Amazon customers.
About the team
The team owns four key pillars that are foundational for Amazon financing globally. Those four pillars are eligibility models, CX models and experimentation, financial pricing, and financial incrementality.
We are open to hiring candidates to work out of one of the following locations:
Arlington, VA, USA | Cupertino, CA, USA | Seattle, WA, USA
BASIC QUALIFICATIONS
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/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.
As an Applied Scientist within Worldwide Installments, you will be responsible for building machine learning models and pipelines with direct customer impact. These models represent a core capability for Worldwide Installments and businesses across Amazon. Your work will directly impact customers by influencing how they interact with financing options to make purchases. You will work across functions including data engineering, software development, and business to induce data driven decisions at every level of the organization.
Key job responsibilities
This role will be responsible for:
• \tDeveloping production machine learning models and pipelines for the WW Installments Competitive Pricing team that directly impact customers.
• \tApply expertise in machine learning to develop large-scale production systems that are deployed across Amazon businesses.
• \tIdentify business opportunities, define and execute modeling approach, then deliver outcomes to various Amazon businesses with an Amazon-wide perspective for solutions.
• \tLead the implementation of production ML from a scientific perspective including identifying potential risks, key milestones, and paths to mitigate risks.
• \tIdentifying new opportunities to influence business strategy and product vision using data science and machine learning.
• \tContinually improve the WW Installments ML roadmap automating and simplifying whenever possible.
• \tCoordinate support across engineers, scientists, and stakeholders to deliver ML pipelines, analytics projects, and build proof of concept applications.
• \tWork through significant business and technical ambiguity delivering on analytics roadmap across the team with autonomy.
A day in the life
We directly solve customer problems and our output has direct customer impact. As a result, we're always working on a novel customer problem that has never been researched let alone solved. You might start a day developing a model that will be surfaced on Amazon. From there, you will join a design review and provide feedback to more jr scientists. This is followed by a business review of your model with high ranking stakeholders (Director/VP). Finally, day will end consulting with a partner that will use one of our models to deliver brand new products or experiences for Amazon customers.
About the team
The team owns four key pillars that are foundational for Amazon financing globally. Those four pillars are eligibility models, CX models and experimentation, financial pricing, and financial incrementality.
We are open to hiring candidates to work out of one of the following locations:
Arlington, VA, USA | Cupertino, CA, USA | Seattle, WA, USA
BASIC QUALIFICATIONS
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/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.
Created: 2024-06-12
Reference: 2657674
Country: United States
State: Washington
City: Seattle
ZIP: 98109
About Amazon
Founded in: 1994
Number of Employees: 1600000
Website: https://www.amazon.com/
Career site: https://www.amazon.jobs/en/
Instagram: https://www.instagram.com/amazon/
LinkedIn: https://www.linkedin.com/company/amazon/
Facebook: https://www.facebook.com/Amazon
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