Audio Annotation Analyst - Pindrop

What you’ll do

As an Audio Annotation Analyst on the Research team, you will review and annotate audio recordings, video content, and associated interaction data to support the development, evaluation, and improvement of Pindrop's fraud detection, authentication, and deepfake detection technologies. Your assignments will span audio and video annotation projects based on evolving Research priorities and team needs.

Your primary responsibility will be to produce accurate, consistent, and high-quality annotations across a variety of Research projects. You will also support targeted investigations by reviewing interactions, identifying anomalies, and documenting observations that help Research Scientists better understand model performance and real-world customer interactions.

You will…

• Review and annotate audio recordings, video content, and associated interaction data, assigning accurate labels based on project-specific guidelines and classification criteria.
• Apply established classification criteria to identify potential fraud indicators, authentication outcomes, characteristics of human-generated versus synthetic content, and other attributes relevant to Research projects, including intent recognition when applicable.
• Apply annotation guidelines consistently across large datasets, review existing labels for discrepancies, and help maintain high-quality datasets for model development and evaluation.
• Flag interactions that are difficult to classify or fall outside established guidelines, document observations, and collaborate with Research Scientists to resolve edge cases.
• Support Research investigations by reviewing audio and video interactions to identify potential issues such as background noise, audio quality degradation, IVR process gaps, or unexpected model behavior.
• Conduct targeted interaction and metadata reviews to support customer inquiries, model evaluations, and evolving Research priorities.
• Maintain accurate annotation records and summarize findings, recurring patterns, and classification inconsistencies to support Research analysis and model improvements.
• Handle sensitive audio, video, and interaction data responsibly, following established privacy, security, and confidentiality guidelines.

Who you are

You are…

• Exceptionally attentive to detail, with strong listening and observational skills to identify subtle differences in audio, video, and interactions.
• Comfortable with focused, repetitive review work and able to maintain accuracy and consistency across large volumes of data.
• Able to follow detailed guidelines while exercising sound judgment when encountering ambiguous or unfamiliar situations.
• Organized, self-driven, and able to document classification decisions and observations clearly while managing assigned workloads.
• Curious about new technologies, forms of fraud, and synthetic or manipulated media.
• Adaptable and comfortable transitioning between audio and video annotation projects, learning new tools, and applying different classification standards as Research priorities evolve.

Your skill-set

Must have…

• Excellent listening and observational skills, strong attention to detail, and the ability to apply defined annotation and classification guidelines accurately to audio and video content.
• Ability to perform high-volume, repetitive annotation and review tasks while maintaining quality and consistency.
• Ability to recognize inconsistencies and ambiguous cases, document findings clearly, and escalate questions appropriately.
• Familiarity with spreadsheets (Excel, Google Sheets) or comparable tools for organizing, categorizing, and reviewing data.
• Clear written communication skills and the ability to work independently, manage priorities, and meet timelines in a remote environment.

Nice to have…

• Experience with data annotation, audio or video labeling, transcription, quality assurance, or qualitative data review.
• Familiarity with fraud detection, authentication, voice biometrics, trust and safety, or contact center and IVR workflows.
• Understanding of synthetic speech, replay attacks, deepfakes, or machine learning labeling tasks such as intent recognition or speech analysis.
• Experience with annotation platforms, structured review tools, or basic data-querying concepts such as SQL

What’s in it for you

At Pindrop, Research sits at the intersection of AI, voice, fraud, identity, and customer experience. This is an opportunity to work with real-world interaction data and contribute directly to the development and evaluation of technologies that protect enterprises and their customers from increasingly sophisticated fraud and identity threats.

Your annotations and analytical findings will help Research teams build more reliable datasets, evaluate model performance, identify emerging attack patterns, and continuously improve Pindrop's technologies.

You'll have the opportunity to…

• Develop firsthand knowledge of voice intelligence, fraud prevention, authentication, and deepfake detection.
• Support high-quality datasets that improve machine learning models and research methods.
• Review audio, video, and interaction data across different customer environments, use cases, and projects.
• Partner with Research Scientists and other stakeholders to connect annotation findings to model reliability, product decisions, and better customer experiences.
• Develop critical thinking, data analysis, written communication, and problem-solving skills while gaining exposure to emerging technologies.