Role at a glance
- Job function
-
AI & Data Data Science
- Salary
- $136K – $184K/yr
- Location
- Austin, Texas, United States
- Work arrangement
- On-site
- Experience
- 3+ years of data scientist experience
- Education
- degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or...
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Role Summary
This Data Scientist role on the OTS ANCHOR team within Amazon's WW IT Operations & RME organization focuses on models for IT operations forecasting, severity triaging, and anomaly detection. The role also involves productionizing ML models on AWS and communicating findings to stakeholders and senior leaders.
What You'll Do
- Design, develop, and deploy machine learning models for IT operations forecasting, including incident volume prediction, capacity...
- Build and maintain severity classification and intelligent triaging models for IT service tickets across global regions
- Develop anomaly detection systems to identify emerging patterns in operational data
- 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
- Communicate findings, model performance, and recommendations to stakeholders and senior leaders through written documents and presentations
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Bachelor's degree in a quantitative field and 3+ years of data science experience with SQL, Python, or statistical software.
Required
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS,...
- 3+ years of data scientist experience
- Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance,...
- Experience with statistical models e.g. multinomial logistic regression
- Experience building and deploying production machine learning models (classification, regression, time-series forecasting, anomaly...
Preferred
- 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,...
- 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
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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
About the company
amazon
Large Enterprise
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.