Annotation - Retail

Role Overview

The Retail Annotation SME is responsible for supervising annotation teams, ensuring project quality, training new annotators, and acting as the domain expert for retail-specific labeling projects. The SME bridges the gap between client guidelines, annotation operations, and quality assurance. Collaborate cross-functionally with project managers, data scientists, and client stakeholders to align on annotation schema and best practices.

Key Responsibilities

• Serve as the

  in-house SME

  for all retail annotation types (bounding box, segmentation, attribute tagging, etc.) with hands-on support for data labeling projects.

• Interpret and translate client guidelines

  into clear, actionable instructions for annotators.

• Train, mentor, and supervise

  a team of data annotators (525 members).
• Conduct

  training sessions

  on annotation tools, retail domain standards, and quality processes.
• Establish

  annotation best practices

  , define quality benchmarks, and track KPIs (accuracy, throughput).
• Perform

  spot checks, audits, and feedback reviews

  to maintain > 98% annotation accuracy.
• Collaborate with project managers and clients to

  refine annotation guidelines

  .
• Maintain detailed documentation of SOPs & training handbooks.
• Support continuous improvement via RCA

  and retraining programs

  .
• Stay updated on

  emerging retail AI applications & Annotation Techniques

  (e.g., shelf analytics, planogram verification, customer behavior tracking).

Required Skills & Qualifications

• Graduate in any discipline with experience in

  Retail Management, AI/ML, or related fields

  .
• 5–8 years of experience in

  data annotation or retail data operations

  , with at least 2 years in a supervisory/training role.
• Strong command of

  annotation tools

  (e.g., Labelbox, SuperAnnotate, CVAT, Roboflow).
• Proficiency in

  quality control, feedback delivery, and documentation

  .
• Excellent interpersonal, mentoring, and leadership skills.
• Experience in onboarding, training, and nurturing diverse teams.
• Strong analytical mindset to identify pattern-level issues in annotations.
• Over 3 years of hands-on experience in Agile/Scrum environments, delivering high-quality annotation outputs and contributing to retail projects involving SKUs, product attributes, and customer interactions.

Additional Skills (Good-to-Have)

• Experience working with

  retail AI/ML datasets

  for product detection, shelf compliance, or shopper analytics.
• Prior experience in

  client-facing QA or training program design

  .
• Familiarity with

  Python labeling frameworks or data formats (COCO, YOLO, Pascal VOC)

  .
• Analytical mindset, able to optimize processes for scalability and efficiency.
• Commitment to ongoing learning of new annotation methodologies and industry standards.
• Deep understanding of

  retail products, merchandising, and store layouts

  .

  Role & responsibilities

Preferred candidate profile