Data Science Intern

1stdibs 1stdibs

The Most Beautiful Things on Earth

1stdibs is the world’s largest online luxury marketplace for one-of-a-kind products. It has become the go-to source for the world’s leading interior designers and consumers to find antiques, vintage furniture, jewelry, vintage fashion and fine art.

Backed by Benchmark Capital, Insight Ventures Partners, Index Ventures, Spark Capital and Alibaba, 1stdibs is a unique blend of expert curators and seasoned Internet executives from companies including eBay, Gilt, Google, FreshDirect,, Venmo, and Twitter.


1stdibs is seeking a Data Science Intern that will support our analytics team develop compelling points of view using data gathered around the most beautiful things on Earth.

Our Data Science program focuses on the core areas of our e-commerce marketplace, including acquisition of demand, optimization of supply and development of site features.  In addition, you will support the co-development of our data warehouse and BI infrastructure and paid attribution modeling.

To succeed, you will become intimately familiar with our data sources and infrastructure and also become an expert in an arsenal of analytical tools, including R, SQL, Looker and Google Analytics.  You will develop and refine your critical thinking skills through the exploration of business questions around supply & demand, customer intent, and inventory mix.

You will also have the opportunity to take ownership of independent projects that can make a significant impact on 1stdibs’ growth and success.

This position is a paid internship, with the prospect of full-time employment.

What you’ll do

  • Develop a mastery of 1stdibs site interactions data via BigQuery
  • Explore the creation of both predictive and inference models that inform process improvements and feature prioritization
  • Build and maintain reporting automation, leveraging R and SQL for data extraction and processing

What you’ll bring

  • Master’s in a quantitative field, data science or business analytics
  • Proficient with various analytical toolkits; SQL and R are a must
  • Comfortable with large relational databases; MySQL, Amazon Redshift, Google BigQuery
  • Experience with ensemble methods for classification, bayesian statistics, and data mining
  • Knowledge of cloud computing frameworks such as Apache Spark and Elastic Mapreduce
  • Comfort working in a fast-paced, cross-functional environment
  • Strong time management and communication skills

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