Data Scientist, OTS - Data ANCHOR Team

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 work streams — 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.

• - 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 product ionize ML models via automated pipelines using AWS services (Sage Maker, 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 (Service Now 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:

• 1. Medical, Dental, and Vision Coverage
• 2. Maternity and Parental Leave Options
• 3. Paid Time Off (PTO)
• 4. 401(k) Plan

• - 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)

• - 2+ years of data visualization using AWS Quick Sight, 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, Fire Hose, 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…