Data Analyst I

Jobtailor; Mumbai; On-site; INR 180,000 - 300,000; Full time

Job summary

Jobtailor is seeking detail-oriented data annotators in Mumbai to work on cross-format labeling tasks for computer vision datasets. You will annotate documents, images, video, and audio, draw boxes and landmarks, and flag tampering or spoof artifacts under clear guidelines.

You will collaborate with ML engineers, review peers, and help improve annotation tools and guidelines. Training is provided, and precision in repetitive tasks is essential to maintain dataset quality for face recognition and

Qualifications

• Attention to detail and strong observational skills.
• Ability to focus on repetitive tasks while maintaining accuracy.
• Basic understanding of computer vision/ML concepts (training provided).
• Comfortable using web-based annotation tools (training provided).
• Clear written and verbal communication skills to describe edge cases.

Responsibilities

• Data annotation across multiple formats (documents, images, video, audio) following project guidelines.
• Identify and label document elements (e.g., names, photos, signatures, holograms) and flag potential tampering.
• Annotate manipulated regions in deepfake and image tamper datasets.
• Tag liveness indicators and spoof artifacts in PAD datasets.
• Draw bounding boxes, facial landmarks, and expression labels for face recognition tasks.
• Apply time-based labels in video for frame-level PAD/deepfake detection.
• Document edge cases and suggest improvements to annotation guidelines.
• Review peer annotations, check consistency, and ensure quality standards.
• Collaborate with ML engineers and data scientists to improve dataset quality and tools.

Skills

Attention to detail

Repetitive task focus

Basic ML concepts

Annotation tools proficiency

Clear communication

Job description

Responsibilities

• Data annotation across multiple formats (documents, images, video, audio) following project guidelines.
• Identify and label document elements (e.g., names, photos, signatures, holograms) and flag potential tampering.
• Annotate manipulated regions in deepfake and image tamper datasets.
• Tag liveness indicators and spoof artifacts in PAD datasets.
• Draw bounding boxes, facial landmarks, and expression labels for face recognition tasks.
• Apply time-based labels in video for frame-level PAD/deepfake detection.
• Document edge cases and suggest improvements to annotation guidelines.
• Review peer annotations, check consistency, and ensure quality standards.
• Collaborate with ML engineers and data scientists to improve dataset quality and tools.

Requirements

• Attention to detail and strong observational skills.
• Ability to focus on repetitive tasks while maintaining accuracy.
• Basic understanding of computer vision/ML concepts (training provided).
• Comfortable using web-based annotation tools (training provided).
• Clear written and verbal communication skills to describe edge cases.