Quality Lead(Mapping & Labelling)

Role Purpose The purpose of this role is to increase revenue, maximize process efficiency & cost-effectiveness, and ensure excellent customer experience, through effective supervision of daily operations and personnel, contract compliance, resource optimization and capability development within an account.

Collaborate with leaders to provide strategic and operational plans associated with the account

Plan the strategy for the coming years by identifying new geographies for alternate revenue streams

Ensure a deep enough understanding of clients’ individual experiences to head off potential issues before they become problems

Ensure all SLA parameters are met in the account and maintain a green card at all times

Review and drive appropriate actions/ systemic changes on internal and external audit findings to ensure no major non-compliances are cited

Monitor and review the account on various delivery parameters to ensure quality delivery as per budget and timelines

Understand customer goals and key performance metrics and ensure exceeding those goals throughout the project

Ensure a green card for all accounts in terms of performance and quality

Monitor and review delivery dashboards/ MIS across accounts to track progress and identify potential red flags

Participate and share account performance across operational, quality and fulfillment parameters with internal and external stakeholders

Lead and manage project escalations, potential risks or early warning signs on project delivery to eliminate any revenue leakage

Ensure regular invoicing as per the contract terms and condition

Forecast and track key account metrics

Timely submission of invoices to the client as defined in the SOW

Provide information required and resolve any invoicing issues raised by the client

Evaluate performance with key metrics (accuracy, customer service metrics etc.)

Set direction for the team, track progress against targets through regular cadence calls and course correct as require

Drive the focus of the team on quality and adherence to contract compliance processes

Drive and implement structured cadence around quality, both process and transactional

Cadence with delivery lead to ensure margins are met and the account numbers are at par to what is committed

Weekly calls with WFM to ensure resource optimization, compliance to the manpower numbers agreed in the contract, future planning in case of ramp ups etc.

Resource Allocation & Retention

Conduct effective resource planning to maximize the productivity of resources (people, technology etc.)

Review and monitor resource planning and fulfillment in line with account requirements and costs of delivery

Optimize manpower and minimize leakages by working closely with delivery head

Ensure retention by offering relevant trainings and certifications of all allocated resources

Lead one-on-one floor connect and other engagement activities to improve stickiness of the delivery team

Collaborate and influence internal key stakeholders to manage and resolve issues to ensure fulfillment and flawless delivery of projects

Essential Hiring Skills

Statistical Analysis and Data-Driven Problem Solving: Demonstrated ability to analyze large volumes of operational data to identify defect trends, calculate key performance metrics (such as Inter-Rater Reliability, precision, and recall), and make evidence-based decisions to improve overall dataset health.

Root Cause Analysis (RCA) Methodology: Proven expertise in systematically investigating quality regressions. The candidate must be able to trace errors back to their origin—whether stemming from tool limitations, policy ambiguity, or human error—and implement effective Corrective and Preventive Actions (CAPA).

Cross-Functional Communication and Alignment: Strong verbal and written communication skills required to bridge the gap between technical and non-technical teams. The candidate must be capable of presenting complex quality reports to engineering stakeholders while providing clear, actionable feedback to operational workforces.

Quality Framework Design and Standardization: Experience developing, implementing, and maintaining rigorous audit frameworks and Standard Operating Procedures (SOPs). The ability to define statistically significant sampling strategies that balance rigorous quality checks with operational throughput.

Team Calibration and Performance Coaching: The ability to lead regular calibration sessions to align multi-tiered teams on subjective guidelines. Must possess the coaching skills necessary to design structured feedback loops that effectively correct annotator behavior and reduce recurring defect rates.

Responsibilities The Quality Lead is responsible for defining, measuring, and upholding the data integrity standards for machine learning annotation workflows. This role involves designing robust quality assurance (QA) frameworks, managing team performance metrics, and driving continuous improvement initiatives. The ideal candidate will act as the final gatekeeper for data accuracy, ensuring that all deliverables meet strict engineering thresholds before model training.

Key Competencies and Responsibilities:

Quality Assurance & Audit Frameworks: Design and manage statistical sampling strategies to evaluate large-scale annotation datasets. Oversee the daily operations of QA auditors to ensure rigorous, unbiased reviews of ground-truth data.

Metrics Tracking & Reporting: Monitor, analyze, and report on primary quality metrics, including Inter-Rater Reliability (IRR), precision, recall, and overall defect rates. Develop and maintain dashboards to provide ongoing visibility to cross-functional stakeholders.

Root Cause Analysis (RCA): Lead deep-dive investigations into quality regressions or sudden drops in annotator performance. Identify whether errors stem from tooling defects, ambiguous policy documentation, or operational oversight, and implement corrective actions.

Feedback Loops & Calibration: Establish structured, actionable feedback mechanisms for the annotation workforce to correct behavioral trends and reduce recurring errors. Lead regular calibration sessions with Policy Leads and Engineering to align on quality definitions and subjective edge cases.

Process Optimization: Identify bottlenecks in the QA workflow and collaborate with operational managers to streamline auditing processes, ensuring high-quality output without severely impacting overall throughput.

Core Qualifications:

Proven experience in quality management, data operations, or a highly analytical QA role.

Strong proficiency in statistical analysis, data sampling methodologies, and identifying defect trends.

Detail-oriented mindset with the ability to communicate complex quality issues clearly to both technical and non-technical teams.

Good to have Hiring Skills Practical experience with, or formal certification in, continuous improvement methodologies such as Lean, Six Sigma (Green Belt or above), or Kaizen, Prior exposure to industry-standard data annotation platforms and an understanding of how tool design, hotkeys, and user interface ergonomics directly impact annotator fatigue and error rates.