Grailed is seeking a Staff Data Scientist to enhance personalization, recommendations, and product marketplace improvements.
The ideal candidate should understand both the user experience and the business implications of data.
The role requires expertise in dimension reduction techniques, predictive modeling, and advanced analytic methods.
This position will collaborate across Data, Product, Engineering, and Marketing to create data products that assist buyers and sellers.
Responsibilities include forming a high-level perspective on organizational objectives and identifying business problems that can be solved with data solutions.
The candidate will establish best practices for model training, evaluation, and maintenance.
They will own the deployment of models into production, ensuring integration with existing data pipelines in Snowflake using DBT.
The role involves evaluating model performance, using A/B testing, and mining user data for personalization opportunities.
The candidate will develop and maintain data models in Snowflake and create ML models using Python.
They will enhance personalization through user-to-user mapping and utilize search technologies for product discovery.
The role includes analyzing message content for potential fraudulent activities and collaborating with various stakeholders to meet their data needs.
Requirements:
Candidates must have 8+ years of relevant experience in a data or quantitative role, preferably in a startup or high-growth environment.
A graduate degree in data science, analytics, mathematics, machine learning, computer science, or a related field is preferred.
Experience in marketplace, e-commerce, or fashion/retail domains is preferred.
Familiarity with web and app product environments is advantageous.
Strong communication skills for non-technical, cross-functional collaboration are essential.
The ability to convey complex data concepts to diverse audiences is required.
Proven expertise in advanced statistical modeling, causal inference, and machine learning algorithms is necessary.
Expert-level proficiency in Python for data manipulation and model development is required.
Practical experience with vector databases and embeddings is preferred.
Experience with Snowflake for SQL and data warehousing is preferred.
Familiarity with DBT for building modular data transformations is preferred.
Experience with Git for collaborative code development is preferred.
Candidates should have experience in designing and optimizing personalization and recommendation products at scale.
Experience in building models for assessing item quality and using NLP on unstructured text is preferred.
Experience in modeling time-series forecasts for market trends and demand prediction is preferred.
Benefits:
The hiring range for this position is $179,600 - $210,000 USD, plus benefits.
Benefits include a 401K plan, paid time off, dental, medical, vision, disability, and life insurance options.
The company considers various factors for determining starting pay, including work location, role, skills, experience, and market demands.
