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Job Responsibilities:
Leads multi-team AI training data operations and executes end-to-end ops strategy. Optimizes delivery through process standardization, analytics, and technology, while ensuring quality, client satisfaction, and team development. Co-leads operational excellence with the Senior Manager, Quality.Key Responsibilities
- Ops strategy execution: Turn business goals into operating plans, OKRs, and runbooks across multiple teams and vendors.
- Standardization & scale: Build and roll out SOPs, playbooks, and templates; reduce variance and drive consistent results across programs.
- Analytics & insights: Define core dashboards and metrics; review performance and convert data into actions for speed, quality, and cost.
- Technology & automation: Partner with Ops Tech/Engineering to improve tools, integrations, and automation (e.g., workflows, APIs, RPA).
- Quality partnership: Co-own excellence with the Senior Manager, Quality—align on guidelines, audits, corrective actions, and training.
- Workforce & capacity: Plan capacity across sites and vendors; optimize shifts, skills, onboarding, and certification paths.
- Vendor strategy: Set expectations and SLAs; review performance, drive improvements, and make scale/exit recommendations.
- Client satisfaction: Support executive governance, planning, and reviews; ensure delivery commitments align with scope and policy.
- Financial stewardship: Build budgets and forecasts; manage margins and change orders; align commercial and delivery outcomes.
- Risk, compliance, and security: Own ops risk management and readiness for audits; ensure privacy and data-handling policies are followed.
- Org & talent development: Manage managers (L1) and senior ICs (P-level); hire, coach, set goals, and grow succession pipelines.
- Cross-functional leadership: Coordinate with Sales/Account, Quality, Product/Ops Tech, and Vendor Management to meet client and business goals.
Additional Job Details:
Education
- Bachelor’s degree or equivalent experience in business, operations, data/engineering, or a related field.
Experience
- 5–8 years in operations or program delivery in AI data, content review, labeling/annotation, or adjacent domains.
- 4–6 years in operations leadership (leading managers/teams, portfolio or multi-workstream environments).
- Track record driving standardization, analytics, tooling/automation, and vendor performance at scale.
Skills
- Program/portfolio planning and governance across multiple teams.
- People leadership: goal setting, coaching, delegation, and performance feedback.
- Clear communication with senior client stakeholders and internal executives.
- Strong use of spreadsheets, PM/task boards, and BI dashboards; familiarity with SQL/ETL concepts is a plus.
- Quality mindset with practical use of SOPs, QA gates, and acceptance criteria.
- Sound judgment on scope, time, cost, and quality; confident negotiation and escalation.
- Comfortable working with global, distributed teams (advanced English).
Scope & Autonomy (L2 Alignment)
- Leads multiple teams/disciplines and sets operating rhythms and standards across programs.
- Makes day-to-day and medium-term strategic decisions; escalates only non-standard or high-impact items.
- Direct line management for L1 managers and senior ICs; strong influence across Quality, Tech, and Vendor partners.
- Co-leads operational excellence with the Senior Manager, Operations.