Lead operational excellence for Frontier AI's India site, managing a team of over 500 data associates. This role requires a strategic leader focused on continuous improvement and flawless daily execution against challenging service level agreements.

This is a proactive, not a maintenance, position. The ideal candidate will challenge existing processes, enhance efficiency, elevate performance, and significantly improve operations. Success hinges on navigating ambiguity, seamlessly shifting between strategic planning and tactical problem-solving, and making sound judgments.

Frequent engagement with senior leadership on strategy, risk assessment, and performance outcomes is a key expectation.

Take full ownership of the operational P&L for the Hyderabad site, driving cost efficiencies while maintaining or exceeding quality SLAs for all active programs. Develop workforce plans in collaboration with Finance, aligning labor capacity with demand forecasts and implementing flexible staffing strategies to meet SLAs during volume shifts.

Define and implement a multi-year operational strategy for Data Services, anticipating changes in program volume, automation adoption, and workforce composition to strategically position the site for new workstreams. Lead cross-functional initiatives with Engineering, Product, and Program teams to define tooling needs, influence product roadmaps based on operational feedback, and conduct structured user acceptance testing for feature releases.

Oversee the site's quality framework, establishing feedback loops to identify defect root causes, implement corrective actions swiftly, and escalate systemic issues with data-backed proposals to relevant teams. Design scalable processes that minimize headcount growth by leveraging automation, tooling enhancements, and workflow redesign for consistent throughput gains.

Build and mentor a high-performing leadership team, setting clear performance standards, rigorously assessing talent, and ensuring a robust succession plan for all critical roles. Foster a data-driven culture where decisions are informed by statistical analysis and process changes are validated through A/B testing.

Cultivate an engagement model that measurably improves associate retention and engagement scores year-over-year, implementing targeted interventions based on attrition drivers. Serve as the site's primary executive liaison, translating operational data into strategic insights, contributing to business reviews, preparing strategic documents for decision-making forums, and proactively highlighting risks with mitigation strategies.

Act as a force multiplier across the cluster by sharing best practices, standardizing processes, and contributing to organizational initiatives that elevate performance across peer sites.

Demonstrated experience managing large, diverse teams across multiple locations or in an acting operations management capacity. Proven ability to manage P&Ls and achieve strong financial results.

Experience communicating complex information effectively to senior stakeholders and influencing decisions. This includes experience in driving process improvements through automation and data analysis. A minimum of one year in capacity planning, operations planning, business analysis, or a related field is required.

Experience aligning work with an organization's long-term strategy and objectives is essential. Preferred qualifications include experience in natural language data labeling, annotation, or related data markup fields, or editorial writing. Familiarity with Six Sigma, Lean techniques, or experience in reliability/maintenance environments is beneficial.

Strong analytical skills, meticulous attention to detail, and effective communication are valued. Experience with automation, version control tools, and data analysis tools such as Microsoft Excel and SQL is advantageous. The ability to collaborate effectively across functions and with employees of varying skill sets is crucial.

A Master's degree or equivalent experience in Operations, Computer Science, or a related field is preferred, particularly for those applying quantitative analysis to business challenges.