Operational Analytics Scientist — Drive Big Process Improvements

Amazon Science; Bellevue (WA); On-site; USD 136,000 - 184,000; Full time

Job summary

Amazon Science is seeking a data scientist to derive insights for operational improvement through analytics. The role requires analysis, understanding of the systems workflow, cross-functional communication and issues management.

The successful candidate will build tools and dive deep to identify root causes of system errors and performance issues. They will present findings to business partners to drive improvements and prioritize customer needs, delivering scalable analyses and automated

Qualifications

• 2+ years of data scientist experience.
• 3+ years of data querying languages (SQL) and scripting (Python) experience.
• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience.
• Experience applying theoretical models in an applied environment.

Responsibilities

• Design scalable approaches to support decision making across the business.
• Apply science techniques to solve business problems with unclear solutions.
• Build ML algorithms, NLP, neural networks and related methods.
• Acquire data by building ETL queries.
• Establish scalable automated data analyses processes for large-scale analyses.
• Analyze for trends and input validity by inspecting distributions and anomalies.
• Validate against alternatives, expectations, and KPIs.
• Build relationships with stakeholders and counterparts.

Skills

SQL

Python

R

Matlab

SAS

Machine learning

Statistical modeling

Data analysis

Tools

ETL

Job description

Amazon Science is seeking a data scientist to derive insights for operational improvement through analytics. The role requires analysis, understanding of the systems workflow, cross-functional communication and issues management.

The successful candidate will build tools and dive deep to identify root causes of system errors and performance issues. They will present findings to business partners to drive improvements and prioritize customer needs, delivering scalable analyses and automated