Data Scientist, OTS - Data ANCHOR Team

Amazon Inc.; Seattle (WA); On-site; USD 136,000 - 184,000; Full time

Benefits offered by this job

Medical, Dental, and Vision Coverage

Maternity and Parental Leave Options

Paid Time Off (PTO)

401(k) Plan

Job summary

Amazon Inc. is seeking a Data Scientist to own end-to-end data science charter for IT operations, forecasting demand and capacity, and building intelligent triaging models. You will collaborate across teams to deploy scalable ML solutions and contribute to predictive analytics that improve incident response globally.

The role requires hands-on model development, experimentation, and production readiness using AWS services, along with strong communication to leadership and stakeholders.

Qualifications

• 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab) 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)

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

Skills

SQL

Python

R

SAS

Matlab

Education

Bachelor's degree in statistics / data science / related field

Master's degree in statistics / data science / related field

Tools

SageMaker

Redshift

AWS Glue

EMR

Kinesis

Lambda

Job description

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

Amazon Benefits

• 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.

Veterans, military spouses, and people with disabilities are encouraged to apply.

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