Staff Data Scientist

Position Overview

• Location Type: [Not Specified]
• Job Type: Staff Data Scientist
• Salary: [Not Specified]

Grailed is seeking a Staff Data Scientist to lead efforts in personalization, recommendation systems, and marketplace improvements. The ideal candidate will possess a deep understanding of how data impacts user experience and business operations within the fashion industry, coupled with a robust technical background. This role requires expertise in dimension reduction, predictive modeling (statistical or ML), and advanced analytics. You will collaborate across Data, Product, Engineering, and Marketing teams to build data products that help buyers discover items and sellers maximize their revenue. You will work with data in Snowflake, develop models in Python, partner with ML engineers for data structuring, and align data product development with business goals.

Responsibilities

• Develop a high-level perspective on organizational objectives and identify opportunities for advanced data methods to solve complex business problems.
• Proactively and autonomously identify business problems solvable with data, from proposal to execution, whether through existing or new models.
• Establish best practices for data model training, development, performance evaluation, monitoring, and maintenance.
• Own the deployment of trained models into production in collaboration with Data or ML Engineers.
• Ensure reliable and observable model deployment into Snowflake using DBT, integrating with existing data pipelines and platform infrastructure.
• Maintain version control of code and configurations using Git.
• Evaluate model performance and iterate to improve accuracy and effectiveness, including using A/B testing to validate personalization initiatives and communicating results to stakeholders.
• Mine user data to identify personalization improvement opportunities, defining and tracking relevant KPIs.
• Develop and maintain data models in Snowflake to support analytical and reporting needs, providing insights to business stakeholders.
• Use Python to create ML models and structure resulting data for consumption.
• Develop user-to-user mapping capabilities using graph databases and vector embeddings to enhance personalization.
• Utilize search technologies (e.g., Algolia, AWS OpenSearch) to improve product discovery and personalization.
• Analyze message content to detect fraudulent activities, identifying keywords or phrases associated with scams, off-platform transactions, or phishing attempts.
• Collaborate with product managers, engineers, designers, and business stakeholders to understand data needs and deliver data-driven solutions.

Requirements

• 8+ years of relevant work experience in a data or quantitative role.
• Demonstrated success in a startup, high-growth, or fast-paced organization.
• Graduate degree in data science, analytics, mathematics, machine learning, computer science, or a related field is a plus.
• Experience in marketplace, e-commerce, or fashion/retail domains is preferred.
• Experience with web and app product environments is preferred.
• Demonstrated success in non-technical, cross-functional partner communication.
• Ability to communicate complex concepts and results effectively to diverse audiences, from C-suite to individual contributors.
• Proven expertise in advanced statistical modeling, causal inference, and experiment/test design.
• Working knowledge of machine learning algorithms.
• Expert-level proficiency in Python for data manipulation and analysis.