Applied Scientist, Worldwide Installments

Amazon is hiring an Applied Scientist, Worldwide Installments in Arlington, United States. It pays $143k-$193k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this applied scientist role Builds AI ●●●●: the job is building AI systems.
Level classes it as a senior role.
Amazon has 21,000+ other open roles on Level.
Posted in the last few days.

AI in this role

WW Installments is one of the fastest growing businesses 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 WW Installments, you will be responsible for building machine learning models and pipelines with direct customer impact. These models represent a core capability for WW 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:
• Developing production machine learning models and pipelines for the WW Installments Fraud Detection team that directly impact customers.
• Apply expertise in machine learning to develop large-scale production systems that are deployed across Amazon businesses.
• Identify business opportunities, define and execute modeling approach, then deliver outcomes to various Amazon businesses with an Amazon-wide perspective for solutions.
• Lead the implementation of production ML from a scientific perspective including identifying consumer financial credit and fraud risks, key milestones, and paths to mitigate risks.
• Identifying new opportunities to influence business strategy and product vision using data science and machine learning.
• Continually improve the WW Installments ML roadmap automating and simplifying whenever possible.
• Coordinate support across engineers, scientists, and stakeholders to deliver ML pipelines, analytics projects, and build proof of concept applications.
• Work through significant business and technical ambiguity delivering on analytics roadmap across the team with autonomy.

Basic qualifications

- Master's degree or above in computer science, machine learning, engineering, or related fields
- 3+ years of building models for business application experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Preferred qualifications

- PhD in computer science, machine learning, engineering, or related fields
- 5+ years of building machine learning models or developing algorithms for business application experience
- Experience using Unix/Linux
- Experience in professional software development

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, VA, Arlington - 142,800.00 - 193,200.00 USD annually
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually

How we rate this

Applied Scientist, Worldwide Installments at Amazon rates 87 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Applied Scientist, Worldwide Installments is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $143k-$193k a year.
The role is based in US, VA, Arlington.
The job was posted on October 22, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Also common in applied scientist jobs at this level

Deep learning LLM Generative AI NLP TensorFlow Spark

Pay

This job starts at: $143k
Typical applied scientist job: $172k

This posting starts 17% below the typical applied scientist job. See applied scientist jobs

Want an expert to read your CV for this job?

Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.

Get a free CV review Get an express CV review Check your resume with the ATS resume checker

Get new applied scientist jobs (Builds AI ●●●●) by email

One email a week with the new applied scientist jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.

Free. One email a week. Unsubscribe in one click.