Data Scientist, OTS - Data ANCHOR Team

Amazon is hiring a Data Scientist, OTS - Data ANCHOR Team in Austin, United States. It pays $136k-$184k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this data scientist role Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include SageMaker.
Level classifies it as a mid-level role.
Level lists 21,000+ other open roles at Amazon.
The role was posted in the last few days.

AI in this role

sagemaker

The OTS ANCHOR (Analytics, Insights, and Centralized Hub for OTS Reporting) team is part of the WW IT Operations & RME organization, responsible for delivering data solutions that drive operational excellence across Amazon's global IT infrastructure. We build data pipelines, predictive models, develop analytical intelligence frameworks, and create AI-powered solutions that transform how Amazon manages, triages, and resolves IT operational incidents at scale pointing towards the Letting Data Tell the Story north start vision.

We are seeking a Data Scientist to help own the end-to-end data science charter for critical operational workstreams — from forecasting IT service demand and capacity planning to designing intelligent severity triaging models and building the analytical backbone for agentic AI solutions. You will work backwards from complex operational problems to create models and solutions that directly impact the efficiency and reliability of Amazon's IT operations worldwide.

Key job responsibilities
- Design, develop, and deploy machine learning models for IT operations forecasting, including incident volume prediction, capacity planning, and workforce demand modeling
- Build and maintain severity classification and intelligent triaging models that process thousands of daily IT service tickets across global regions
- Develop anomaly detection systems to identify emerging patterns in operational data, supporting proactive incident prevention
- Apply econometric and statistical methods to measure the impact of operational interventions and inform resource allocation decisions
- Partner with engineering teams to productionize ML models via automated pipelines using AWS services (SageMaker, Step Functions, Lambda, Redshift)
- Design and conduct experiments to empirically validate model performance and operational impact
- Contribute to data quality monitoring frameworks and help maintain standards for operational data integrity
- Collaborate with cross-functional teams (ServiceNow platform, Decision Intelligence, Field Operations) to translate analytical insights into actionable recommendations
- Communicate findings, model performance, and recommendations to stakeholders and senior leaders through written documents and presentations
- Contribute to the team's science roadmap, identifying opportunities to apply ML/AI (including Generative AI) to operational challenges

A day in the life
Amazon Benefits:
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan

Basic qualifications

- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of data scientist experience
- Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- Experience with statistical models e.g. multinomial logistic regression
- Experience building and deploying production machine learning models (classification, regression, time-series forecasting, anomaly detection)

Preferred qualifications

- 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
- Experience managing data pipelines
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with written and verbal communication and presentation

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, TX, Austin - 136,000.00 - 184,000.00 USD annually

How we rate this

Data Scientist, OTS - Data ANCHOR Team at Amazon rates 86 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

Data Scientist, OTS - Data ANCHOR Team is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $136k-$184k a year.
The role is based in US, TX, Austin.
The job was posted on October 26, 2026.
Seniority: mid.
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

SageMaker

Also common in data scientist jobs at this level

LLM Spark Deep learning PyTorch NLP scikit-learn

Pay

This job starts at: $136k
Typical data scientist job: $165k

This posting starts 18% below the typical data scientist job. See data scientist jobs

Questions you could be asked

What's a project where you used SageMaker hands-on?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: SageMaker. 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.

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