Machine Learning Data Associate- Remote, Customer Engagement Technology
Amazon
Description
Application deadline: Dec 10, 2025
Interested in working with data and machine learning? Do you have a passion for customer service? Join our Customer Engagement Technologies automation team in developing language solutions that power self-service and automation across Amazon.
We are seeking an ML Data Associate to join our remote team who will independently drive data initiatives critical to measuring model accuracy and developing automation features. A successful candidate will own end-to-end data workflows, coordinate cross-functionally on mid-sized projects, and mentor peers while identifying process improvements. This role offers the opportunity to make measurable impact through high-quality projects that directly influence our ML model performance and automation capabilities.
Key job responsibilities
- Effectively represent data based customer and associate behavior to improve automation workflows
- Participate in automation solutioning between cross functional teams and validate the launch of proposed solutions
- Deliver results according to project schedules and quality while maintaining SLAs on velocity, productivity and quality
- Independently own and drive small to mid-sized data workstreams with minimal guidance, ensuring clear documentation and measurable outcomes
- Lead cross-functional coordination between Operations, Policy, and Tech teams to execute data initiatives effectively
- Analyze and interpret metrics to shape project decisions, while proactively monitoring quality standards and customer feedback
- Manage data tools independently, identifying improvement opportunities and suggesting process enhancements
- Mentor peers and champion process improvements within the team's scope of work
- Take full ownership of project outcomes while maintaining strong documentation standards
- Drive regular updates and maintain clear communication channels with stakeholders
- Proactively identify and implement local process improvements to enhance team efficiency