Team Manager, AGI-DS
Amazon.com
Amazon is an E-Commerce and Cloud Computing company with headquarters in Seattle, Washington. Since 1995, Amazon has focused on being "the world's most customer centric company."
Key job responsibilities
Manages team size of approximately 25 ML Data Associates.
· Executes plans for team to perform tasks related to multiple ML workflows in a well-defined process area.
· Ensures ML data workflows are quality compliant. Analyzes ML data, SIM issues, and metrics. Highlights trends, gaps, etc. Provides status reports.
· Identifies risks and ensures escalations reach the right people. Adherence to confidentiality and compliance requirements
· Responsible for known SLAs and task completion targets (within provided capacity) for specific customers.
· Works with internal/ external teams and uses his/her knowledge and expertise to execute business goals
· Uses data to set/revisit operational goals and manage activities
· Manages escalation/ complex tickets; analyzes data; highlights trends, gaps, etc.; and reports key metrics
· Presents data in business meetings/reviews
· Design and implement process improvement projects that impact team level performance. Participates in new workflow roll out projects teams.
· Coaches direct reports on demonstrating leadership principles in their role.
· Assigns appropriate challenging work to employees to develop & prepare them for larger roles.
· Provides team guidance on work types and prioritization. Work of team primarily focuses on straightforward, well-defined objectives, but may take on ad hoc and ill-defined requests.
· Devises and implements performance improvement plans for associates. Provides regular coaching and feedback to direct reports with regard to quality, performance, behavior and career development.
· Performance manages team based on metrics & deliverables on a regular basis, and make decisions on hiring & firing.
· Holds team members accountable for performance based on metrics and adherence to rules and guidelines.
About the team
Our team's mission is to provide high-quality labelled data at high-speed and low-cost for machine learning (ML) technologies.
Key job responsibilities
Manages team size of approximately 25 ML Data Associates.
· Executes plans for team to perform tasks related to multiple ML workflows in a well-defined process area.
· Ensures ML data workflows are quality compliant. Analyzes ML data, SIM issues, and metrics. Highlights trends, gaps, etc. Provides status reports.
· Identifies risks and ensures escalations reach the right people. Adherence to confidentiality and compliance requirements
· Responsible for known SLAs and task completion targets (within provided capacity) for specific customers.
· Works with internal/ external teams and uses his/her knowledge and expertise to execute business goals
· Uses data to set/revisit operational goals and manage activities
· Manages escalation/ complex tickets; analyzes data; highlights trends, gaps, etc.; and reports key metrics
· Presents data in business meetings/reviews
· Design and implement process improvement projects that impact team level performance. Participates in new workflow roll out projects teams.
· Coaches direct reports on demonstrating leadership principles in their role.
· Assigns appropriate challenging work to employees to develop & prepare them for larger roles.
· Provides team guidance on work types and prioritization. Work of team primarily focuses on straightforward, well-defined objectives, but may take on ad hoc and ill-defined requests.
· Devises and implements performance improvement plans for associates. Provides regular coaching and feedback to direct reports with regard to quality, performance, behavior and career development.
· Performance manages team based on metrics & deliverables on a regular basis, and make decisions on hiring & firing.
· Holds team members accountable for performance based on metrics and adherence to rules and guidelines.
About the team
Our team's mission is to provide high-quality labelled data at high-speed and low-cost for machine learning (ML) technologies.
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