Global Head of Quality
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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 (ML/AI) 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 easy-to-use, 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 RoleWe are seeking a strategic and hands-on leader to drive quality excellence across our global data annotation and data collection operations. As Global Head of Quality, you will own the end-to-end 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 cross-functional teams in a dynamic, customer-driven 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 AI-assisted quality checks to reduce variance and improve accuracy.
• Collaborate with Product and Engineering to explore automation, pre-annotation, LLM-based quality review, and tooling enhancements.
• Champion a quality-first culture across the organization, embedding quality principles in onboarding, training, and daily execution.

Required Qualifications

• 5+ years of experience in data quality, annotation operations, or related fields, including 2+ years in a leadership capacity.
• Deep familiarity with data annotation workflows and quality control methodologies (manual and automated) across varied data modalities.
• Proven ability to design and scale quality programs across large, distributed teams.
• Strong background in data analysis and reporting, including use of tools such as SQL, Excel, BI platforms, or Python/R for data quality tracking.
• Experience translating customer requirements into operational plans and actionable quality standards.
• Strong people-leadership skills with a track record of building and mentoring high-performing global teams.
• Excellent communication and cross-functional collaboration skills.

Preferred Qualifications

• Experience working with AI/ML teams or supporting model training and evaluation through high-quality human-labeled data.
• Familiarity with regulatory or customer compliance frameworks (e.g., data privacy, bias mitigation).
• Understanding of productivity and quality tradeoffs in scaling projects with freelancers and geographically distributed talent pools.
• Experience deploying quality frameworks for projects involving reinforcement learning, red teaming, or subjective annotation tasks.
• Graduate degree in a relevant field (e.g., Linguistics, Data Science, or Statistics) is a plus.

Salary Range: $150,000-$200,000Salary rates at Innodata vary depending on a wide array of factors, which may include but are not limited to the role, skill set, educational background and geographic location.We are an equal opportunity employer committed to fostering an inclusive, respectful, and diverse workplace. We welcome and encourage applications from individuals of all backgrounds and are dedicated to employment equity and building a team that reflects the diverse communities in which we live and operate.

Seniority level

• Seniority levelExecutive

Employment type

• Employment typeFull-time

Job function

• Job functionQuality Assurance
• IndustriesInformation Services

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