Description

As a Staff Data Scientist, you will develop advanced AI models to enhance operational workflows and customer experiences. You will collaborate with teams to improve product quality verification and drive measurable improvements in accuracy and efficiency.

Requirements

• •6+ years of experience in data science, machine learning engineering, or AI development
• •Deep expertise in applied AI/ML (computer vision, anomaly detection, fraud/risk modeling)
• •Experience in architecturing, deploying, and maintaining AI systems at scale
• •Proficiency in programming languages such as Python
• •Deep understanding of machine learning algorithms, statistical modeling, and data manipulation techniques
• •Experience with data visualization tools and communicating insights effectively
• •Strong problem-solving skills
• •Ability to work independently and collaboratively in a fast-paced, global team environment
• •Experience with cloud platforms (e.g., AWS, GCP, Azure) and MLOps practices
• •Experience building or maintaining customer service chatbot systems
• •Familiarity with database technologies (SQL, NoSQL) and cloud data warehouse (BigQuery/Snowflake)
• •Excellent communication and interpersonal skills
• •Fluency in written and spoken English

Tasks

• •Design and own end-to-end AI/ML solutions for item quality and authenticity detection
• •Analyze images to detect marks, defects, wear, and size inconsistencies
• •Understand text and metadata for brand, sizing, and category anomalies
• •Develop counterfeit and fraud detection models
• •Prototype and iterate on AI models to enhance customer-facing experiences
• •Collaborate with Product and Curation teams to define requirements and integrate AI models
• •Provide insights to improve verification processes
• •Advise on data collection for continuous model improvement and performance monitoring
• •Conduct rigorous model evaluation and A/B testing
• •Ensure seamless deployment and integration of AI models with engineering teams
• •Research advancements in AI, machine learning, deep learning, and computer vision
• •Mentor senior and mid-level data scientists on modeling and data quality
• •Communicate complex technical concepts to technical and non-technical stakeholders

Tools & Technologies

Benefits