Content Analyst & Knowledge Engineer Mgr

Yahoo Mail Content Analyst And Knowledge Engineer

Yahoo Mail is the ultimate consumer inbox with hundreds of millions of users. It's the best way to access your email and stay organized from a computer, phone or tablet. With its beautiful design and lightning fast speed, Yahoo Mail makes reading, organizing, and sending emails easier than ever.

We are a global service organization providing human evaluation and diagnostic services including content analysis and insights, testing and training data, and product quality optimization.

As Content Analysts and Knowledge Engineers, we do human evaluation, content management, data analysis, training data development and evaluation for tuning models, taxonomy and tagging systems, and other information management projects for Yahoo-branded products and applications. Through structured data extraction processes, we transform unstructured data in non-semantic HTML pages into structured data using internal tools and workflows. That transformed structured data helps Yahoo create products that enhance and personalize user experiences.

Our team also plays a critical role in bridging human judgment and AI systems by supporting the development, evaluation, and continuous improvement of Large Language Models (LLMs), Machine Learning (ML) systems, and human-in-the-loop workflows.

You are both a strategic operator and people leader, capable of balancing delivery execution, operational excellence, stakeholder alignment, and team development in a fast-paced, highly cross-functional environment.

Location: Bangalore, Karnataka, India

This is a hybrid role requiring employees to work from the Bangalore office at least 3 days / week.

Your Day

Team Leadership

• Lead and develop a global team of Content Analysts and Knowledge Engineers across disciplines including LLM evaluation, metrics, editorial review, QA, taxonomy, and content operations.
• Manage day-to-day team operations, ensuring high-quality execution, operational consistency, and successful project delivery across multiple concurrent initiatives.
• Forecast resource needs, prioritize workloads, and allocate staffing effectively to meet evolving business priorities and delivery timelines.
• Establish clear operating rhythms, workflows, communication practices, and quality standards to improve efficiency, transparency, and accountability.
• Provide coaching, mentorship, performance management, and career development opportunities to support team growth and progression.
• Build and sustain a collaborative, inclusive, and high-trust team culture focused on continuous improvement and operational excellence.
• Proactively identify and resolve team challenges, conflicts, staffing gaps, and operational risks.
• Develop and optimize human-in-the-loop workflows, including assisted labeling, AI-supported evaluation, and automated quality assurance systems.
• Identify opportunities to integrate AI into operational workflows to improve efficiency, consistency, scalability, and quality outcomes.

You Must Have

• A BA or BS degree. Preferred fields: Linguistics, Computer Science, Library & Information Science, Information Management, or related disciplines.
• 7+ years of relevant professional experience, including people leadership or operational management responsibilities.
• Experience managing or mentoring teams in content operations, annotation, evaluation, taxonomy, ML data workflows, or related disciplines.
• Exceptional organizational, communication, and stakeholder management skills, including the ability to articulate complex technical concepts clearly and effectively.
• Demonstrated ability to lead operational execution across multiple concurrent projects while balancing quality, timelines, and resource constraints.
• Strong analytical, editorial, operational, and business judgment.
• Proven experience collaborating cross-functionally with Engineering, Product, Research, and Operations teams.
• Expertise in taxonomy development, content categorization, and data classification schema.
• Familiarity with prompt engineering, AI-assisted workflows, model evaluation concepts, human-in-the-loop systems, or annotation operations preferred.
• Experience leveraging AI tools and automation to improve operational quality, productivity, and scalability preferred.