IT Operations Data Scientist — Forecasting & AI

Amazon Science; Austin (TX); 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 Science in Austin, TX is seeking a Data Scientist to own end-to-end data science workstreams for IT operations forecasting, anomaly detection, and intelligent triaging models. You will design ML solutions, build data pipelines, and collaborate with cross-functional teams to translate insights into actionable improvements for global IT operations.

Applicants should have 3+ years of data science experience, strong SQL/Python/R skills, and a proven track record deploying production ML

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)

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

Statistical modeling

Data storytelling

Experimentation

Education

Bachelor's degree in quantitative field

Master's degree in quantitative field

Tools

SQL

Python

R

Job description

Amazon Science in Austin, TX is seeking a Data Scientist to own end-to-end data science workstreams for IT operations forecasting, anomaly detection, and intelligent triaging models. You will design ML solutions, build data pipelines, and collaborate with cross-functional teams to translate insights into actionable improvements for global IT operations.

Applicants should have 3+ years of data science experience, strong SQL/Python/R skills, and a proven track record deploying production ML