Senior Manager, Science and BI Lead, WWOS Tech

Amazon is hiring a Senior Manager, Science and BI Lead, WWOS Tech in Seattle, United States. It pays $219k-$296k a year and Level rates it ; you can apply on Level.

Level's read on this job

On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include Sagemaker, MLOps and AI safety.
Level files it as a senior role.
Level lists 22,000+ other open roles at Amazon.
The role was posted in the last few days.

AI in this role

Lead enterprise AI/ML strategy, delivery, and a team of applied scientists to build production machine learning models.

sagemaker

ml-opsai-safetymachine-learningmlopsdata-scienceai-strategyteam-management

Have you ever wanted to solve a mystery or be part of solving a case? Are you fascinated by detective stories or crime shows on TV? Do you love to manage huge volumes of data, have a science background and enjoy solving complex problems?

WWOS Tech is transforming into an AI-first security technology organization, and we're seeking an exceptional Applied Science Manager to anchor this transformation. As the Science & BI Lead, you'll own the enterprise AI/ML roadmap, lead an organization of scientists and BIEs, and deliver production AI and ML models that will generate 1M+ efficiency hours annually.

Key job responsibilities
Lead AI/ML Strategy & Delivery

- Own the enterprise AI/ML roadmap across UNITE (theft detection, investigation automation), PRISM (operational disruption, risk management) and other WWOS Tech products
- Deliver net-new production AI models by EOY 2026 aligned to WWOS SPS goals: reduce theft/fraud loss from 0.30% to 0.19% of GMS and transform incident preparedness from reactive to proactive.
- Establish AI/ML delivery standards: model quality gates, bias detection, responsible AI compliance (Amazon Trust principles, EU AI Act), and production readiness criteria
- Build centralized model registry, shared experimentation platform (SageMaker), and MLOps infrastructure in partnership with Data Engineering

Build & Scale High-Performing Teams

- Lead Science & BI pillar within WWOS Tech: grow Science team over next 18 months, manage 3 BIE managers overseeing BIEs across EESN, Ops Disruption, and Business Reporting teams

- Recruit, onboard, and retain top AI/ML talent in a highly competitive market; develop career paths for Scientists, ML Solutions Architects, and BIEs transitioning to AI-enabled strategic advisors

- Drive AI literacy across all of WWOS organization: 100% AI-trained by EOY 2026 across Technical, Leadership, and Cross-Skill tracks

- Establish operating rhythm: weekly Science pillar sync, bi-weekly cross-pillar integration reviews, monthly AI portfolio health inspections
Partner with Business & Technical Leaders

- Translate ambiguous business problems into AI/ML solutions through direct partnership with field leaders, program vertical leaders, and WWOS senior leadership.

- Represent WWOS Tech in Amazon-wide AI/ML forums: AWS AI partnerships, responsible AI governance, GOS AI forums

Drive Responsible AI & Governance

- Ensure all AI models touching sensitive security data meet Amazon's responsible AI bar and evolving regulatory requirements (GDPR, EU AI Act)
- Implement bias detection, model explainability and human-in-the-loop mechanisms for high-risk applications
- Conduct quarterly AI risk assessments with Legal, InfoSec, and Privacy teams; maintain AI model inventory and compliance dashboard
- Partner with AI Ethics & Governance Specialist to establish enterprise-wide responsible AI frameworks

About the team
We are a team that cares about your work-life balance, while challenging you to solve problems at high scale. You will be part of a strong team in a fast-paced, start-up environment where agile development is embraced and innovation is encouraged. You will get support and resources from some of the smartest people in the industry to continue your personal and professional growth. You'll be joining a fun team that prides itself on a great work environment with an inclusive group of people that loves working together towards a common goal and make history in launching a new strategic service in the industry.

Basic qualifications

- 10+ years of building large-scale machine learning and AI solutions at Internet scale experience
- Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)
- Experience building large-scale machine learning and AI solutions at Internet scale
- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
- Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track

Preferred qualifications

- 10+ years of practical work applying ML to solve complex problems for large-scale applications experience
- 5+ years of hands-on work in big data, machine learning and predictive modeling experience
- 5+ years of people management experience
- PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)
- Experience in practical work applying ML to solve complex problems for large scale applications
- Experience working with big data, machine learning and predictive modeling
- Experience in people management
- Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.
- Experience with Java, C++, or other programming language, as well as with R, MATLAB, Python, or an equivalent scripting language
- Experience researching actual applications

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.

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, WA, Seattle - 218,800.00 - 295,900.00 USD annually

How we rate this

Senior Manager, Science and BI Lead, WWOS Tech at Amazon rates 90 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. Open the description and count.

Key facts

Senior Manager, Science and BI Lead, WWOS Tech is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $219k-$296k a year.
The role is based in US, WA, Seattle.
The job was posted on October 16, 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.

Skills and AI tools this role asks for

ML OpsAI SafetyMachine learningMLOpsData ScienceAI StrategyTeam ManagementSagemaker

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
How do you think about the risk of an AI system in this kind of role failing silently?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where mlops was part of your work. What did you do?
Tell me about a project where data science was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: ML Ops, AI Safety, Machine learning, MLOps, and Data Science. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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 Check your resume with the ATS resume checker