Manager I, ML Data Operations , Manager I, ML Data Operations
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Manager I, ML Data Operations , Manager I, ML Data Operations
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Full-time
bachelor degree
Posted 1d ago
~40 hrs/week
Responsibilities
The manager will lead a team of 20-25 associates to meet operational goals, manage business metrics, and ensure high-quality data annotation for ML models. They are responsible for process improvements, capacity planning, and developing team members through coaching and performance management.
Requirements
Candidates must have a graduate degree and 4-6 years of work experience, including at least one year in direct people management. Proficiency in data analysis, Microsoft Excel, and the ability to manage multiple competing priorities are essential.
Full job description
Whenever a customer visits Amazon and types in a query or browses through product categories, Amazon Search services go to work. Search Ops team helps Search services in providing a better customer search experience by delivering quality data annotation to help improve AI/ML models driving these services.
Our vision is to create business value by delivering high quality data at scale. We look to provide easy and scalable labeling solution to support search that are high quality, cost efficient, and secure. Our vision is to enable improvement in the search experience for our customers, by accurately determining labels for products targeted by the search queries received. We collaborate closely with several machine learning (ML) applied science teams that develop and test ML models to improve the quality of semantic matching, ranking, computer vision, image processing, and augmented reality.
To support our vision, we need exceptionally talented, bright, and driven people. Duties will include ensuring that standards for productivity and quality assurance are met by your team, taking part in planning, organizing and directing the work of Team Members or others, outline procedures and instructions on work received, make time estimates on new jobs received, ensuring utilization of team is high, mentor and train new/existing team members. If this opportunity excites you, join us to build innovative solutions and shape the future of search
Key job responsibilities As a Team Manager, ML Data Ops, you will be responsible for meeting operational and business goals by leading a team of 20 to 25 associates having expertise in one or more processes/functions and proficient in languages other than English. You will also be a driving initiative across sites for process improvements, SoP and guidelines formulation, diving deep to provide data insights as and when required. Your key responsibilities will include (but not limited to) the below:
Executes and makes plans to deliver business metrics, and uses data to set/revisit operational goals and manage activities Manages escalations; analyzes data; highlights trends, gaps, etc.; and reports key metrics Prepares data in business meetings/reviews and presents to senior managers and stakeholders Plans capacity and commits to volume by managing resources, queue, shift management, cross training, and leave management Owns and prioritizes work allocation based on business needs with a daily/monthly frequency Owns the output quality of the process managed Performs deep-dive analysis and creates COEs (Correction of Error) based on the deviation, problem, root cause, and solutions Initiates and leads process improvement projects, presents solution proposals, and implements them to other applicable/in- scope operational areas Participates and provides adequate support in business reviews with mid-level and senior leadership Participates in new- process onboarding, i.e., new process/ experiments with complete documentation Participates in or owns modules of solution- building in business process setup, operations front-line setup, cross-functional process activity, tool-build documentation, etc. Demonstrates understanding of performance and leadership bar, applies it effectively to team members and to new hiring decisions Builds robust launch plans for new team members & owns progress tracking of new joiners through administration of launch plans as a mechanism Provides regular coaching and feedback to direct reports Devises and implements performance improvement plans for associates as applicable Identifies and works with top performers for talent development and creates a leadership pipeline for own level * Willingness to work with sensitive issues, including but not limited to: Adult content, Religious and philosophically sensitive issues, tobacco, weapons and other potentially offensive products
Basic Qualifications:
- Graduate degree in any discipline - 4-6 years’ work experience with at least 1 year in managing people directly - Demonstrated high attention to detail and proven ability to manage multiple competing priorities simultaneously - Well versed in employee development and performance management skills and strategies including performance reviews, goal setting, and providing feedback - Ability to work cross-functionally and with employees across teams with different skill sets - Proven ability to report and analyze data. Confident in using Microsoft Package (especially Excel at Intermediate to Advanced level) - Confident to work with large volumes of data - Demonstrated ability to initiate & drive process improvements
Preferred Qualifications:
- Experience in e-commerce, retail or advertising - Working knowledge of Machine learning - Certified or Green belt trained in Lean Six Sigma - Familiarity with tools like QuickSight and Tableau
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.
Related keywords
ML Data OperationsSearch OpsData AnnotationAI/ML ModelsProcess ImprovementOperational GoalsBusiness MetricsCapacity PlanningPerformance ManagementLean Six SigmaQuickSightTableauE-commerceData InsightsQuality AssuranceTeam Leadership