Global Head of Quality

Innodata (NASDAQ: INOD) is a leading data engineering company. Prestigious companies across the globe turn to Innodata for help with their biggest data challenges. By combining advanced machine learning and artificial intelligence (MLAI) technologies, a global workforce of subject matter experts, and a high[1]security infrastructure, we’re helping usher in the promise of clean and optimized digital data to all industries. Innodata offers a powerful combination of both digital data solutions and easytouse, highquality platforms. Our global workforce includes over 3,000 employees in the United States, Canada, United Kingdom, Philippines, India, Sri Lanka, Israel, and Germany. Interested in joining us?

About the Role

We are seeking a strategic and handson leader to drive quality excellence across our global data annotation and data collection operations. As Global Head of Quality, you will own the endtoend strategy and execution for data quality for one or more delivery units, including the development of robust frameworks, performance measurement systems, and feedback loops that ensure the delivery of accurate, consistent, and actionable data to our customers.

You will play a critical role in supporting the design and scoping of new workflows, analyzing data quality across diverse projects and translating insights into operational improvements. This position requires a deep understanding of AI data lifecycle needs, strong analytical skills, and the ability to lead crossfunctional teams in a dynamic, customerdriven environment.

Key Responsibilities

• Lead the global data quality strategy for data annotation and collection workflows, ensuring alignment with customer use cases and delivery objectives.

• • Design and evolve quality assurance frameworks tailored to diverse data types (e.g., text, audio, video, image), annotation schemas, and project constraints.

  • • Define and track quality metrics and KPIs and build reporting tools and dashboards to drive transparency and accountability across global teams.

    • • Analyze quality data and customer feedback to identify failure patterns, root causes, and opportunities for process optimization.

      • • Support scoping and workflow design for new data collection and labeling projects, ensuring feasibility of quality controls from the outset.

        • • Partner with Solutions, Delivery, and Customer Success teams to translate customer requirements into scalable quality protocols.

          • • Oversee a global team of quality analysts, QA leads, and training specialists, setting goals and supporting their professional development.

            • • Establish continuous improvement loops, leveraging error analyses, rater performance data, and AIassisted quality checks to reduce variance and improve accuracy.

              • • Collaborate with Product and Engineering to explore automation, preannotation, LLMbased quality review, and tooling enhancements.

                • • Champion a qualityfirst culture across the organization, embedding quality principles in onboarding, training, and daily execution.