Labeling Specialist QA - Fashion & Shopping

Who we are:

Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are an AI technology solutions provider-of-choice for 4 out of 5 of the world’s biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine.

By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of subject matter experts, and a high-security infrastructure, we’re helping usher in the promise of AI. Innodata offers a powerful combination of both digital data solutions and easy-to-use, high-quality platforms.

Our global workforce includes over 5,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany. We’re poised for a period of explosive growth over the next few years.

About the Role:

Innodata is building a specialized team of shopping and fashion specialists to support our clients with data analysis tasks in fashion, home decor, and beauty. As a domain expert and enthusiast, you’ll put your expertise to work reviewing, coaching, and reporting on the work of a team of SME Labeling Specialists. Your work in helping to ensure accurate classification and tagging of shopping products will help improve product discovery, filtering, and personalization for users. You’ll work directly with the client as an extension of their team. Your efforts will also contribute to a more diverse and inclusive experience for shoppers!

Requirements

Basic Qualifications:

• In-depth Industry Knowledge: Strong understanding of fashion, home decor, and beauty trends, terminology, and product categories.
• Fantastic Attention to Detail: Ability to accurately tag and classify products with precision to ensure data integrity. Ability to accurately distinguish a wide range of highly stratified colors and patterns/gradients.
• Trend Awareness: Up-to-date on current styles, seasonal trends, and popular brands to improve tagging relevance.
• Understanding of Consumer Preferences: Insight into how consumers search and filter products within these categories.
• Good communication and interpersonal skills: Ability to collaborate on a team in a professional environment and work directly with our client.
• Analytical Skills: Ability to review quality data and extract key themes. Able to generate clear and concise reports to inform stakeholders.
• Bachelor’s degree in art/fashion, graphic design, merchandising, marketing, or similar field.
• Experience workingin fashion/beauty/decordesign, marketing, or a related industry function.

Preferred Qualifications:

• Data Labeling Experience: Prior experience in data annotation or labeling tasks, particularly within fashion, home decor, or beauty verticals.
• Familiarity with E-commerce Standards: Experience with ecommerce platforms and product catalog structures.

What we offer:

• Collaborative culture – and key tools enabling it

Key Responsibilities:

1. Data Labeling and Classification:
   1. Be an expert in the accurate tagging and classification of attributes for products in the fashion, home decor, and beauty categories.
   2. Ensure data integrity through precise labeling practices.
2. Inclusivity Assessment:
   1. Evaluate merchants based on inclusive criteria, focusing on size ranges, skin tone representation, and gender inclusivity.
   2. Review merchant websites and marketing materials for diverse representation across ages, ethnicities, body types, and abilities.
3. Body Type and Skin Tone Categorization:
   1. Assign appropriate body type ranges and skin tone categories to images, supporting inclusivity in product representation.
   2. Identify and label edge cases, providing feedback for continuous improvement.
4. Brand Identification and Classification:
   1. Analyze raw text data to determine brand representation and classify brands based on established tiering criteria.
   2. Conduct web searches for accuracy in brand identification and categorization.
5. Studio Shot Labeling:
   1. Categorize images into “Studio,” “Lifestyle,” or “Lifestyle > IRL” based on the context and setting.
6. Trusted Merchant List (TML) Auditing:
   1. Review and audit merchants against criteria that reflect quality and reliability, contributing to enhanced product discovery for users.

Other Requirements

1. Dedicated home workspace with high-speed internet